Podcasts about Preset

Quad Cortex vs. Moer GE300 vs. Zoom GFX-8 (von 2003)... nur in lustig. Wer wird gewinnen? Wir lassen zufällig generierte Preset sounds unserer liebsten digitalen Geräte gegeneinander antreten. In den Ring gehen: Quad Cortex von Neural Dsp für den Justin, Moer GT300 für den Fabian und das legendäre Zoom GFX-8 von 2003 für Robin. Welches würdet ihr euch nach dieser Folge kaufen? :P Viel spaß beim hören.

In episode 395, we are thrilled to host local producer and DJ Agropol; tune in as he presents his latest release, "Preset", and treats us to an…

I put out a request to my VIP email community a couple of weeks ago for their help with some market research. I always want to know what you're struggling with the most and how I can best support you on your style journey. And the results of that project were pretty eye-opening.   I heard complaint after complaint that they were wasting way too much time trying to get dressed in the morning and, more often than not, they just end up defaulting to their go-to-outfit uniform. Can you relate?   So what if I told you there is a very simple solution to both of these challenges and it would take you an hour (or less) to start implementing it?   Allow me to introduce the concept of preset outfits! No, I'm not talking about done-for-you, outfit of the day guides you can buy from other stylists. And I'm not talking about the productivity hack of picking out your clothes the night before. I'm talking about building your own custom outfit library of looks that will make it easy and exciting to get dressed for every occasion on your calendar!   I've mentioned this concept on the podcast before, but today, we're taking a deep-dive into why preset outfits are the BEST way to ensure you can get ready efficiently and feel good as you go about your day! Let's make your life a whole lot easier, shall we?   FREE 5-MIN PERSONAL STYLE QUIZ: https://herstylellc.com/quiz HER STYLE BLOG: https://herstylellc.com/blog HER STYLE ON INSTAGRAM: https://www.instagram.com/heatherriggsstyle/ JOIN THE WAITLIST FOR HER STYLE COLLECTIVE: http://herstylellc.com/collective   Related Episodes: 105 - Decisions, Decisions… Choosing Quality Fabrics and Picking Outfits Faster In the Morning 91 - How To Recreate the Cute Outfits You See Online (Step By Step) 72 - Create Better Outfits Using These 3 Design Principles 42 - How To Maximize Your Wardrobe (+ My Honest Thoughts On the Stylebook App!) 9 - 10 Time-Saving Tips To Look Put Together FAST

If you've worked on data problems, you probably have heard of Airflow and Superset, two powerful tools that have cemented their place in the data ecosystem. Building successful open-source software is no easy feat, and even fewer engineers have done this back to back. In part 2 of the conversation, we talk about Max's journey in open source. Segments:    (00:03:27) “Project-Community Fit” in Open Source    (00:08:31) Fostering Relationships in Open Source    (00:10:58) Dealing with Trolls    (00:13:40) Attributes of Good Open Source Contributors    (00:20:01) How to Get Started with Contributing    (00:27:58) Origin Stories of Airflow and Superset    (00:33:27) Biggest Surprise since Founding a VC-backed Company?    (00:38:47) Picking What to Work On    (00:41:46) Advice to Engineers for Building the Next Airflow/Superset?    (00:42:35) The 2 New Open Source Projects that Max is Starting    (00:52:10) Challenges of Being a Founder    (00:57:38) Open Sourcing Ideas Show Notes: Part 1 of our conversation: https://softwaremisadventures.com/p/maxime-beauchemin-llm-ready Max on LinkedIn: https://www.linkedin.com/in/maximebeauchemin/ SQL All Stars: https://github.com/preset-io/allstars Governator: https://github.com/mistercrunch/governator Stay in touch:

If you've worked on data problems, you probably have heard of Airflow and Superset, two powerful tools that have cemented their place in the data ecosystem. Building successful open-source software is no easy feat, and even fewer engineers have done this back to back. In Part 1 of this conversation, we chat about how to adapt to the LLM-age as engineers.   Segments: (00:01:59) The Rise and Fall of the Data Engineer (00:11:13) The Importance of Executive Skill in the Era of AI (00:13:53) Developing the first reflex to use AI (00:17:47) What are LLMs good at? (00:25:33) Text to SQL (00:28:19) Promptimize (00:32:16) Using tools LangChain (00:35:02) Writing better prompts   Show Notes: - Max on Linkedin: https://www.linkedin.com/in/maximebeauchemin/ - Rise of the Data Engineer: https://medium.com/free-code-camp/the-rise-of-the-data-engineer-91be18f1e603 - Downfall of the Data Engineer: https://maximebeauchemin.medium.com/the-downfall-of-the-data-engineer-5bfb701e5d6b - Promptimize: https://github.com/preset-io/promptimize   Stay in touch:

Immergetevi nella nostra nuovissima sezione 'Soluzioni Audio' e scoprite configurazioni hi-fi, home theatre e outdoor che cambieranno il modo in cui ascoltate la musica. Dai un'occhiata ai nostri Preset esclusivi per massimizzare le performance delle vostre casse acustiche Garvan con gli amplificatori. Siamo qui per guidarvi nella scelta della soluzione audio perfetta, sia che siate appassionati di musica, cinefili, o amanti del bel suono.#GarvanAudioExperience #RivoluzioneSonora #QualitàDelSuonoSuperiore

You can always watch the full episode on YT to see the EQ curves and everything else we do to the tone: https://youtu.be/hnNmL_g3cV0Welcome to our second Episode of our new podcast with my good friend & master metal mixer Hjalle! We're talking mixing, metal and life and invites you and your questions inside my studio, hope you enjoy!In this EP we're getting hands on and doing a deep dive on how to nail that Strat Djent Tone, a listeners question from our guy J Vanderwerff over at https://www.youtube.com/c/TempleGuitars who also provided us with some files to work with, big thanks dude! Hope you enjoy!In the next episode we will get into the thall tone as best we can & other fun stuff!Download link for the presets we made (or just copy the settings from the video):https://www.buymeacoffee.com/adamroxner/e/212749Links from the episode:Hjalle: https://www.instagram.com/hjalmaralmgren/Nick Broomhall (Strat Djent tone): https://www.youtube.com/@nickbroomhallmusicAaru (Thall Tone): https://youtu.be/zKSXilRLZU0?si=R7f_PeQMM9PWxIwGSome of my plugins and gear:"Nocturnal Bass": https://bit.ly/3GTiVHQUsing "Runeforge Fenrir" amp modeller: https://solemntones.com/products/runeforge-fenrir?sca_ref=4830910.UNOigXPrqX&sca_source=YouTube

Take your imagination for a ride with this episode featuring Sarina Dahlan, author of the fantastical and touching Four Cities trilogy, including the already-released books RESET and PRESET. She joined fellow author Joe Moldover and Nick Eskey from San Diego's Mysterious Galaxy Bookstore for a lively discussion about publishing genres, memory research, and all things books! Hosted by Trisha Blanchet

Re - Broadcast https://en.wikipedia.org/wiki/Operation_Dark_Winter    

Leo discusses nourishing ourselves during the holidays instead eating more, drinking more and engaging more. We also discuss seasonal affective disorder or SAD.Sponsor:Is there something interfering with your happiness or is preventing you from achieving your goals? https://betterhelp.com/leo and enjoy 10% off your first month and start talking to mental health professional today!! 1-on-1 Coaching: If you want go from feeling hopeless to hopeful, lonely to connected and like a burden to a blessing, then go to 1-on-1 coaching, go to www.thrivewithleo.com. Let's get to tomorrow, together. National Suicide Prevention Lifeline988Teen Line (Los Angeles)800-852-8336The Trevor Project (LGBTQ Youth Hotline)866-488-7386National Domestic Violence Hotline800-799-SAFE [800-799-7233]Crisis Text LineText "Connect" to 741741 in the USALifeline Chathttps://suicidepreventionlifeline.org/chat/International Suicide Hotlines: http://www.suicide.org/international-suicide-hotlines.htmlhttps://www.nowmattersnow.org/skillshttps://sobermeditations.libsyn.com/ www.suicidesafetyplan.com https://scaa.club/

Summary Building a data platform that is enjoyable and accessible for all of its end users is a substantial challenge. One of the core complexities that needs to be addressed is the fractal set of integrations that need to be managed across the individual components. In this episode Tobias Macey shares his thoughts on the challenges that he is facing as he prepares to build the next set of architectural layers for his data platform to enable a larger audience to start accessing the data being managed by his team. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team. You specify the customer traits, then Profiles runs the joins and computations for you to create complete customer profiles. Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack (https://www.dataengineeringpodcast.com/rudderstack) You shouldn't have to throw away the database to build with fast-changing data. You should be able to keep the familiarity of SQL and the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date. With Materialize, you can! It's the only true SQL streaming database built from the ground up to meet the needs of modern data products. Whether it's real-time dashboarding and analytics, personalization and segmentation or automation and alerting, Materialize gives you the ability to work with fresh, correct, and scalable results — all in a familiar SQL interface. Go to dataengineeringpodcast.com/materialize (https://www.dataengineeringpodcast.com/materialize) today to get 2 weeks free! Developing event-driven pipelines is going to be a lot easier - Meet Functions! Memphis functions enable developers and data engineers to build an organizational toolbox of functions to process, transform, and enrich ingested events “on the fly” in a serverless manner using AWS Lambda syntax, without boilerplate, orchestration, error handling, and infrastructure in almost any language, including Go, Python, JS, .NET, Java, SQL, and more. Go to dataengineeringpodcast.com/memphis (https://www.dataengineeringpodcast.com/memphis) today to get started! Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics. Trusted by teams of all sizes, including Comcast and Doordash, Starburst is a data lake analytics platform that delivers the adaptability and flexibility a lakehouse ecosystem promises. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data. Want to see Starburst in action? Go to dataengineeringpodcast.com/starburst (https://www.dataengineeringpodcast.com/starburst) and get $500 in credits to try Starburst Galaxy today, the easiest and fastest way to get started using Trino. Your host is Tobias Macey and today I'll be sharing an update on my own journey of building a data platform, with a particular focus on the challenges of tool integration and maintaining a single source of truth Interview Introduction How did you get involved in the area of data management? data sharing weight of history existing integrations with dbt switching cost for e.g. SQLMesh de facto standard of Airflow Single source of truth permissions management across application layers Database engine Storage layer in a lakehouse Presentation/access layer (BI) Data flows dbt -> table level lineage orchestration engine -> pipeline flows task based vs. asset based Metadata platform as the logical place for horizontal view Contact Info LinkedIn (https://linkedin.com/in/tmacey) Website (https://www.dataengineeringpodcast.com) Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ (https://www.pythonpodcast.com) covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast (https://www.themachinelearningpodcast.com) helps you go from idea to production with machine learning. Visit the site (https://www.dataengineeringpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com (mailto:hosts@dataengineeringpodcast.com)) with your story. To help other people find the show please leave a review on Apple Podcasts (https://podcasts.apple.com/us/podcast/data-engineering-podcast/id1193040557) and tell your friends and co-workers Links Monologue Episode On Data Platform Design (https://www.dataengineeringpodcast.com/data-platform-design-episode-268) Monologue Episode On Leaky Abstractions (https://www.dataengineeringpodcast.com/abstractions-and-technical-debt-episode-374) Airbyte (https://airbyte.com/) Podcast Episode (https://www.dataengineeringpodcast.com/airbyte-open-source-data-integration-episode-173/) Trino (https://trino.io/) Dagster (https://dagster.io/) dbt (https://www.getdbt.com/) Snowflake (https://www.snowflake.com/en/) BigQuery (https://cloud.google.com/bigquery) OpenMetadata (https://open-metadata.org/) OpenLineage (https://openlineage.io/) Data Platform Shadow IT Episode (https://www.dataengineeringpodcast.com/shadow-it-data-analytics-episode-121) Preset (https://preset.io/) LightDash (https://www.lightdash.com/) Podcast Episode (https://www.dataengineeringpodcast.com/lightdash-exploratory-business-intelligence-episode-232/) SQLMesh (https://sqlmesh.readthedocs.io/) Podcast Episode (https://www.dataengineeringpodcast.com/sqlmesh-open-source-dataops-episode-380) Airflow (https://airflow.apache.org/) Spark (https://spark.apache.org/) Flink (https://flink.apache.org/) Tabular (https://tabular.io/) Iceberg (https://iceberg.apache.org/) Open Policy Agent (https://www.openpolicyagent.org/) The intro and outro music is from The Hug (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Love_death_and_a_drunken_monkey/04_-_The_Hug) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/) / CC BY-SA (http://creativecommons.org/licenses/by-sa/3.0/)

The holiday season is all about lists, but will YOU stay on YOUR OWN priority list? The Holiday Preset Mini-Package will help you take small but powerful steps to care for yourself and achieve your health goals, even at this most hectic time of year! Keeping your own well-being front and center will enable you to enjoy some key transformations yet in 2023, while setting you up for enhanced health and flourishing in 2024 and beyond! This transformation is achieved through: ·      One (1) 90-Minute 1:1 coaching session by Zoom or phone to establish your goals and a realistic plan tailored to your needs ·      Either two (2) 25-Minute follow-up sessions or one (1) 60-minute follow-up session to check in on progress, obstacles, and adjustments ·      Following introductory session, you'll get worksheets, handouts and other resources targeted to your goals and preferences ·      Between-session messaging, including 2 emergency 10-minute voice messaging conversations o   Topics to be addressed in 1-on-1 sessions and other communication include goal-setting, motivation, nutrition, movement, stress reduction, holiday hurdles including overwhelm, travel tips, purpose exercises, and starting the new year out right – all customized for you! ·      All aspects and components of the program must be utilized on or before December 30, 2023; all participants will receive advanced registration for all 2024 programs offered by Whole Life Workshop/Wellness While Walking during the first quarter of the new year ·      Cost for the Holiday Preset Mini is $497 ·      Act now to save your spot – email me at wellnesswhilewalking@gmail.com and ask about availability and how to save $50!    

If you think you know ChatGPT, think again. There's been recent leaks and new features that will change the way we use ChatGPT. We're uncovering the latest features, upcoming updates, and insightful predictions about how ChatGPT will shape the way we work, learn, and interact in the future.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions about ChatGPTUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTimestamps:[00:02:27] Overview of new unofficial features in ChatGPT[00:05:25] History of GPT technology[00:12:17] ChatGPT features coming soon[00:14:23] Preset knowledge cut off dates[00:19:06] Multimodal chat allows diverse input and output[00:23:16] All Tools mode expands ChatGPT capabilities[00:26:06] Future internet: Multimodal interaction with up-to-date information[00:29:37] Future of work: remote, hybrid, collaborativeTopics Covered in This Episode:1. Timeline of ChatGPT Development2. Features and Use Cases of ChatGPT3. Announcement of Future ChatGPT Updates4. Discussion on Remote Work and CollaborationKeywords:future of work, remote work, hybrid work, in-person work, collaboration, language models, ChatGPT, OpenAI, collaborative tool, Google Docs, competitiveness, market, affordability, developers, Developers Conference, prompt course, prompt polish course, specific mode, Browse with Bing, internet querying, advanced data analysis, modes and tools, image generation, knowledge cutoff, leaks, outdated knowledge, generative AI, ChatGPT, multimodality, artificial general intelligence (AGI), All Tools mode. Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

Here I describe my method for creating a macro using equalizer, compressor and normalize presets in Audacity, which can be used repeatedly to get consistent results, as long as you use the same voice, microphone and recording location. This is the sample of the equalizer setting I use with a Sennheiser MB2 Pro headset: This is the waveform for this episode before applying the Compressor. This is the waveform for this episode after applying the equalizer discussed earlier, the Compressor at threshold -31dB, noise floor -40dB and ratio 2:1. No make-up gain at the Compressor. Finally, Normalize to peak amplitude of -12dB. I was wrong in the show to say that I had been using "Amplify," in fact I have been using "Normalize."

Timestamps 0:00 - Unity Engine goes off on the deep end 16:12 - FleaMarket rep exploit gets patched 23:59 - Streets can't support the player count 30:20 - Church's first PKM find 38:44 - Fighting Kaban on Streets 52:22 - An interesting new quest 1:17:22 - Is the weight system overtuned? 1:50:12 - Making the Preset system work 2:06:03 - Church has fell off, for real for real Get featured in our next episode! Leave us a message here: https://anchor.fm/scavtalk/message Join the Discord! - https://discord.gg/T9QA2DuFcP Church1x1 - Twitter https://twitter.com/Church1x1 GigaBeef - YT https://www.youtube.com/Gigabeef - Twitter https://twitter.com/Gigabeef --- Send in a voice message: https://podcasters.spotify.com/pod/show/scavtalk/message Support this podcast: https://podcasters.spotify.com/pod/show/scavtalk/support

Re- https://en.wikipedia.org/wiki/Operation_Dark_Winter

The Cross References Podcast with Luke Taylor: Episode 89 “Today's conspiracy theories are tomorrow's headlines.” That's what I told Youtube when they deleted one of my episodes recently for spreading conspiracy theories. Well, Youtube probably won't like what I'm sharing today, either. There's an acronym you need to know: W-E-F. You'll learn what it stands for today. Could their plans be setting up the kingdom of the Antichrist in the near future? We'll discuss that and more today on the CR podcast.   0:00 - Intro 2:45 - Another Important Acronym- WEF 10:15 - The Great Preset 15:00 - the Bible's Vision of the Future   If you want to get in touch with me, send an email to crossreferencespodcast@gmail.com Hosted by Luke Taylor 

It's not enough for leads and prospects to be content with your content! Get the powerful Groove AI platform to start wowing customers and climbing search rankings!Sign up by visiting https://bisnisapps.com/preset-prompt-engineering-by-groove-ai BisnisApps Website https://bisnisapps.com/ Phone +62 812 5380 6707 Email support@bisnisapps.com

MLOps Coffee Sessions #167 with Maxime Beauchemin, Treating Prompt Engineering More Like Code. // Abstract Promptimize is an innovative tool designed to scientifically evaluate the effectiveness of prompts. Discover the advantages of open-sourcing the tool and its relevance, drawing parallels with test suites in software engineering. Uncover the increasing interest in this domain and the necessity for transparent interactions with language models. Delve into the world of prompt optimization, deterministic evaluation, and the unique challenges in AI prompt engineering. // Bio Maxime Beauchemin is the founder and CEO of Preset, a series B startup supporting and commercializing the Apache Superset project. Max was the original creator of Apache Airflow and Apache Superset when he was at Airbnb. Max has over a decade of experience in data engineering, at companies like Lyft, Airbnb, Facebook, and Ubisoft. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // Related Links Max's first MLOps Podcast episode: https://go.mlops.community/KBnOgN Test-Driven Prompt Engineering for LLMs with Promptimize blog: https://maximebeauchemin.medium.com/mastering-ai-powered-product-development-introducing-promptimize-for-test-driven-prompt-bffbbca91535https://maximebeauchemin.medium.com/mastering-ai-powered-product-development-Test-Driven Prompt Engineering for LLMs with Promptimize podcast: https://talkpython.fm/episodes/show/417/test-driven-prompt-engineering-for-llms-with-promptimizeTaming AI Product Development Through Test-driven Prompt Engineering // Maxime Beauchemin // LLMs in Production Conference lightning talk: https://home.mlops.community/home/videos/taming-ai-product-development-through-test-driven-prompt-engineering --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, blogs, newsletters, and more: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Max on LinkedIn: https://www.linkedin.com/in/maximebeauchemin/ Timestamps: [00:00] Max introducing the Apache Superset project at Preset [01:04] Max's preferred coffee [01:16] Airflow creator [01:45] Takeaways [03:53] Please like, share, and subscribe to our MLOps channels! [04:31] Check Max's first MLOps Podcast episode [05:20] Promptimize [06:10] Interaction with API [08:27] Deterministic evaluation of SQL queries and AI [12:40] Figuring out the right edge cases [14:17] Reaction with Vector Database [15:55] Promptomize Test Suite [18:48] Promptimize vision [20:47] The open-source blood [23:04] Impact of open source [23:18] Dangers of open source [25:25] AI-Language Models Revolution [27:36] Test-driven design [29:46] Prompt tracking [33:41] Building Test Suites as Assets [36:49] Adding new prompt cases to new capabilities [39:32] Monitoring speed and cost [44:07] Creating own benchmarks [46:19] AI feature adding more value to the end users [49:39] Perceived value of the feature [50:53] LLMs costs [52:15] Specialized model versus Generalized model [56:58] Fine-tuning LLMs use cases [1:02:30] Classic Engineer's Dilemma [1:03:46] Build exciting tech that's available [1:05:02] Catastrophic forgetting [1:10:28] Promt driven development [1:13:23] Wrap up

Summary For business analytics the way that you model the data in your warehouse has a lasting impact on what types of questions can be answered quickly and easily. The major strategies in use today were created decades ago when the software and hardware for warehouse databases were far more constrained. In this episode Maxime Beauchemin of Airflow and Superset fame shares his vision for the entity-centric data model and how you can incorporate it into your own warehouse design. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team. You specify the customer traits, then Profiles runs the joins and computations for you to create complete customer profiles. Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack (https://www.dataengineeringpodcast.com/rudderstack) Your host is Tobias Macey and today I'm interviewing Max Beauchemin about the concept of entity-centric data modeling for analytical use cases Interview Introduction How did you get involved in the area of data management? Can you describe what entity-centric modeling (ECM) is and the story behind it? How does it compare to dimensional modeling strategies? What are some of the other competing methods Comparison to activity schema What impact does this have on ML teams? (e.g. feature engineering) What role does the tooling of a team have in the ways that they end up thinking about modeling? (e.g. dbt vs. informatica vs. ETL scripts, etc.) What is the impact on the underlying compute engine on the modeling strategies used? What are some examples of data sources or problem domains for which this approach is well suited? What are some cases where entity centric modeling techniques might be counterproductive? What are the ways that the benefits of ECM manifest in use cases that are down-stream from the warehouse? What are some concrete tactical steps that teams should be thinking about to implement a workable domain model using entity-centric principles? How does this work across business domains within a given organization (especially at "enterprise" scale)? What are the most interesting, innovative, or unexpected ways that you have seen ECM used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on ECM? When is ECM the wrong choice? What are your predictions for the future direction/adoption of ECM or other modeling techniques? Contact Info mistercrunch (https://github.com/mistercrunch) on GitHub LinkedIn (https://www.linkedin.com/in/maximebeauchemin/) Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ (https://www.pythonpodcast.com) covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast (https://www.themachinelearningpodcast.com) helps you go from idea to production with machine learning. Visit the site (https://www.dataengineeringpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com (mailto:hosts@dataengineeringpodcast.com)) with your story. To help other people find the show please leave a review on Apple Podcasts (https://podcasts.apple.com/us/podcast/data-engineering-podcast/id1193040557) and tell your friends and co-workers Links Entity Centric Modeling Blog Post (https://preset.io/blog/introducing-entity-centric-data-modeling-for-analytics/?utm_source=pocket_saves) Max's Previous Apperances Defining Data Engineering with Maxime Beauchemin (https://www.dataengineeringpodcast.com/episode-3-defining-data-engineering-with-maxime-beauchemin) Self Service Data Exploration And Dashboarding With Superset (https://www.dataengineeringpodcast.com/superset-data-exploration-episode-182) Exploring The Evolving Role Of Data Engineers (https://www.dataengineeringpodcast.com/redefining-data-engineering-episode-249) Alumni Of AirBnB's Early Years Reflect On What They Learned About Building Data Driven Organizations (https://www.dataengineeringpodcast.com/airbnb-alumni-data-driven-organization-episode-319) Apache Airflow (https://airflow.apache.org/) Apache Superset (https://superset.apache.org/) Preset (https://preset.io/) Ubisoft (https://www.ubisoft.com/en-us/) Ralph Kimball (https://en.wikipedia.org/wiki/Ralph_Kimball) The Rise Of The Data Engineer (https://www.freecodecamp.org/news/the-rise-of-the-data-engineer-91be18f1e603/) The Downfall Of The Data Engineer (https://maximebeauchemin.medium.com/the-downfall-of-the-data-engineer-5bfb701e5d6b) The Rise Of The Data Scientist (https://flowingdata.com/2009/06/04/rise-of-the-data-scientist/) Dimensional Data Modeling (https://www.thoughtspot.com/data-trends/data-modeling/dimensional-data-modeling) Star Schema (https://en.wikipedia.org/wiki/Star_schema) Database Normalization (https://en.wikipedia.org/wiki/Database_normalization) Feature Engineering (https://en.wikipedia.org/wiki/Feature_engineering) DRY == Don't Repeat Yourself (https://en.wikipedia.org/wiki/Don%27t_repeat_yourself) Activity Schema (https://www.activityschema.com/) Podcast Episode (https://www.dataengineeringpodcast.com/narrator-exploratory-analytics-episode-234/) Corporate Information Factory (https://amzn.to/3NK4dpB) (affiliate link) The intro and outro music is from The Hug (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Love_death_and_a_drunken_monkey/04_-_The_Hug) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/) / CC BY-SA (http://creativecommons.org/licenses/by-sa/3.0/)

6/19/23 Re Broadcast https://en.wikipedia.org/wiki/Operation_Dark_Winter

How to Preset successful communications 

Large language models and chat-based AIs are kind of mind blowing at the moment. Many of us are playing with them for working on code or just as a fun alternative to search. But others of us are building applications with AI at the core. And when doing that, the slightly unpredictable nature and probabilistic nature of LLMs make writing and testing Python code very tricky. Enter promptimize from Maxime Beauchemin and Preset. It's a framework for non-deterministic testing of LLMs inside our applications. Let's dive inside the AIs with Max. Links from the show Max on Twitter: @mistercrunch Promptimize: github.com Introducing Promptimize ("the blog post"): preset.io Preset: preset.io Apache Superset: Modern Data Exploration Platform episode: talkpython.fm ChatGPT: chat.openai.com LeMUR: assemblyai.com Microsoft Security Copilot: blogs.microsoft.com AutoGPT: github.com Midjourney: midjourney.com Midjourney generated pytest tips thumbnail: talkpython.fm Midjourney generated radio astronomy thumbnail: talkpython.fm Prompt engineering: learnprompting.org Michael's ChatGPT result for scraping Talk Python episodes: github.com Apache Airflow: github.com Apache Superset: github.com Tay AI Goes Bad: theverge.com LangChain: github.com LangChain Cookbook: github.com Promptimize Python Examples: github.com TLDR AI: tldr.tech AI Tool List: futuretools.io Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy Sponsors PyCharm RedHat Talk Python Training

Local author Sarina Dahlan's "Preset" imagines a world where what's left of human civilization is highly controlled in order to avoid extinction.

Speculative fiction author, Sarina Dahlan is back with a brand new prequel novel. Tune in to hear about her experiences writing book number two and what she has planned next.Support the show on PatreonSigning up to the Patreon will give you access to the Discord server, where you'll be able to interact directly with Jamie as well as many of the previous agents, authors and editors who have been on the show. You'll also be able to see who the upcoming guests are and put forward questions for Jamie to ask them.WriteMentorGet a whole month with WriteMentor's Hub for free using the coupon code 'Write&Wrong'.The Chosen Ones and Other TropesJamie, Melissa and Noami talk about the best and the worst writing tropes!BookshopClick here to find all of our guests' books as well as the desert island library over at bookshop.org.ZencastrClick on this referral link to get 30% off your first three months with Zencastr.

Get Native Instruments 9 for 99 (2023): https://bit.ly/3MpUFB4 Check out Cherry Audio Preset Packs here: https://cherryaudio.com/products/sounds Season 4 Episode 14 of the Emlyn in the Mix show sees us checking out the brilliant Cherry Audio sound packs for Elka X & Mercury-6 (Retro Waves & Snow Angels) These sound..... keep listening to find out - Also winners of the Emergent Drums competition are announced in this show!! Rap Star by Emlyn (Podcast Intro): https://www.youtube.com/watch?v=BM7Oi89Mi5M PLEASE LEAVE ME A REVIEW on THIS PODCAST!! 5 STARS BABY!!! I just set up an email to contact me on the Podcast!! - emlyninthemix@gmail.com P.S I love you

Time Band Song Length Album Year 19:01:12 Anubis Crimson Stained Romance 06:58 Hitchhiking To Byzantium 2014 19:10:29 Lalu Reset to Preset 06:18 Paint the Sky...

Lord of the Lost - Reset the Preset (ft. Andy LaPlequa), The Damned - The Invisible Man, Self Titled Album - Unicorn Tornado of Hurt, HOME FRONT - Real Eyes, Rubella Ballet - She Rocks Punk, unitcode:machine - This Truth, Damien Hearse - Bloodsucker, Plasmata and Ben Christo with Aly Jados - You Call Him the Devil (Ten Bells - Christo Mix), Mechanical Vein - TAKN (ft. Caustic), She Pleasures HerSelf - Bury Me, NAUT - Dissent, Cathedral in Flames - Not Another Vampire Song, Gothzilla - Faithrape, Long Night - Tick Tock, Fields of the Nephilim - Secrets

In this episode, Jennifer talks to Dylan Silver about the many hats she wears as an actor, writer-director, host, and voiceover artist. She talks about staying humble while also voicing your ambitions, leaning into discomfort, and not letting someone else take your power. They share stories about taking initiative, not waiting for someone else's permission and recognizing that it only takes one person to take a chance on you. They also talk about being curious and honest about what you don't know, that everything is helping all the other things, as well as the importance of going after what you want.  About Dylan: Dylan Silver is an actor, writer-director and host. This year she's a 2022 Women In Film Director Mentee and a 2022 Sundance Lab Fellow with her feature CHAIM'S NOT DEAD. Silver's documentary, A MIND LIKE STILL WATER, debuted on Amazon's Top 5 Must Watch List and is available on all streaming platforms. As a host, you can catch her helping couples DIY their hearts out Tastemade's WEEKEND REFRESH or pumping you with motivation on the app PRESET. As an actor, you'll find her currently starring in YouTube Original's animated show BEHIND THE BEATS, playing an upcoming guest star on the CW's WALKER INDEPENDENCE, and starring in DOWNEAST, now on Showtime. She's also really silly, will going bowling anytime, and wants you to hang out with her dog Bagel. Dylan's IG: @dylansilver19 Dylan's Website: www.dylansilverofficial.com Want to coach with Jennifer? Schedule a session here! https://appt.link/jenniferapple Monologue Sourcing Promo Link! https://empoweredartistcollective.com/podcastpromo Learn more: https://www.empoweredartistcollective.com/podcast EAC IG: @EmpoweredArtistCollective  EAC TikTok: @EmpowerArtistCollective EAC Facebook: https://www.facebook.com/empoweredartistcollective/ Sign up for our newsletter! https://mailchi.mp/8e72e8dcb662/stay-in-touch Check Out Our Merch! https://www.empoweredartistcollective.threadless.com/ Any thoughts you'd like to share? Email us at EmpoweredArtistCollective@gmail.com

Show Notes(01:56) Astasia shared her childhood growing up in Silicon Valley.(05:12) Astasia reflected on her undergraduate education at Stanford - studying Political Science and International Relations.(06:35) Astasia discussed her research at the Graduate Business School with Professor Condoleezza Rice on a case study called "San Leon Energy: Hydraulic Fracturing in Poland" - which explores how to manage the political risks of using a controversial energy extraction technology in the European Union.(09:26) Astasia talked about her year in the UK getting a Master's in Technology Policy at the University of Cambridge's Judge Business School.(12:52) Astasia recalled her experience as an Equity Research Analyst at Baird and Co.(17:49) Astasia mentioned her work at Cisco Investments, driving their cloud-infrastructure M&A and venture investments.(20:58) Astasia shared her thoughts on different M&A frameworks she learned from Cisco.(23:27) Astasia reflected on her decision to join Redpoint Ventures in early 2017, leading investments across developer tools, cloud infrastructure, data/ML infrastructure, AI applications, and cybersecurity.(25:44) Astasia debunked misconceptions about the venture industry.(29:30) Astasia discussed ways to prove her value upfront in potential deals and start forming her investment theses as a new investor.(33:01) Astasia dissected the key factors that triggered her to invest in the Series A of Solo.io and the Series B of LaunchDarkly (in the domain of cloud infrastructure).(38:48) Astasia explained her Series A investment in Hex and Series B investment in Preset (in the domain of data infrastructure).(44:12) Astasia shared advice she had given her portfolio companies in hiring decisions, pricing products, and navigating go-to-market strategy while at Redpoint.(47:36) Astasia walked through her process of writing comprehensive research primers in her Medium blog Memory Leak on wide-ranging topics - from data science notebooks and data orchestration to data pipelining and ML data management.(51:19) Astasia shared the typical challenges she has seen in companies looking to incorporate Product-Led Growth into their go-to-market motion.(54:10) Astasia discussed building a community as a fuel for product-led growth and shared advice to startups thinking about starting their community initiatives.(56:40) Astasia shared advice for hiring good DevRel practitioners.(01:00:15) Astasia shared advice for a smart, driven operator who wants to explore angel investing.(01:03:26) Astasia talked about her current journey as the Founding Partner at Quiet Capital, sitting on its early-stage enterprise team and leading opportunities across pre-seed, seed, Series A, and Series B.(01:05:13) Astasia expanded upon her typical mental checklist to evaluate entrepreneurs and make investment decisions.(01:07:36) Astasia briefly touched on LP fundraising for Quiet Capital to become a "modern venture firm."(01:09:59) Astasia emphasized her enthusiasm for the Data-Centric ML movement.(01:13:41) Closing segment.Astasia's Contact InfoLinkedInMediumTwitterQuiet CapitalWebsiteLinkedInTwitterMentioned ResourcesContentJohn Gannon BlogPeopleSatish Dharmaraj (Redpoint Ventures)Scott Raney (Redpoint Ventures)Amanda Robson (Cowboy Ventures)NotesMy conversation with Astasia was recorded back in April 2022. Since then, many things have happened. I'd recommend:Signing up for her Memory Leak newsletterBrowsing through Quiet Capital's new portfolio careers pageListening to Astasia's appearance on the Data Stack ShowChecking out Quiet Capital's investments in Edge Delta, Diagrid, and OmniLooking at her real-time infrastructure landscape

Episode 480 Hunting Preset Spots Vs Mobile Hunting New SamkoWorkShop Youtube Channel: https://www.youtube.com/channel/UCWz_nsMi-bAhPuG-xU_y7_A Traditional Bowhunting and Wilderness Podcast Youtube Channel: https://www.youtube.com/channel/UCQkiplgkZ_ms1ztYpZKf3IQ Patreon.com/tradbowpodcast tbwpodcast.com The post Episode 480 Hunting Preset Spots Vs Mobile Hunting first appeared on Traditional Bowhunting And Wilderness Podcast.

Summary:In this episode of The Sound Table, we talk about our process of making sample packs and preset packs! We have been making paid sound library for a few years and over the years, we have learned quite a bit about the sound design process, the workflow of finishing and releasing a product, and the importance of costumer service and consistency!Listen to this episode to hear all about how we create top-tier, well respected sample packs and preset packs for Make Pop Music that earn well over six figures every single year. About The Sound Table:Welcome to The Sound Table, where we have chats and conversations with creative people.The Sound Table is a bi-weekly podcast hosted by Make Pop Music that dives into the ins and outs of music production, releasing music as an artist, working within the music industry, marketing your music, and everything in between.Enjoy guest episodes that host different peers and friends from all corners of the industry to talk about their lives and experiences, and dive into episodes featuring the co-hosts, Austin and Miranda, discussing their own journeys, opinions, and thoughts about all things pertaining to music and business.Kick back, relax, and enjoy captivating conversations that will leave you inspired and entertained.Links:Our WebsiteOur YouTube ChannelOur Instagram

About MartinMartin Casado is a general partner at the venture capital firm Andreessen Horowitz where he focuses on enterprise investing. He was previously the cofounder and chief technology officer at Nicira, which was acquired by VMware for $1.26 billion in 2012. While at VMware, Martin was a fellow, and served as senior vice president and general manager of the Networking and Security Business Unit, which he scaled to a $600 million run-rate business by the time he left VMware in 2016.Martin started his career at Lawrence Livermore National Laboratory where he worked on large-scale simulations for the Department of Defense before moving over to work with the intelligence community on networking and cybersecurity. These experiences inspired his work at Stanford where he created the software-defined networking (SDN) movement, leading to a new paradigm of network virtualization. While at Stanford he also cofounded Illuminics Systems, an IP analytics company, which was acquired by Quova Inc. in 2006.For his work, Martin was awarded both the ACM Grace Murray Hopper award and the NEC C&C award, and he's an inductee of the Lawrence Livermore Lab's Entrepreneur's Hall of Fame. He holds both a PhD and Masters degree in Computer Science from Stanford University.Martin serves on the board of ActionIQ, Ambient.ai, Astranis, dbt Labs, Fivetran, Imply, Isovalent, Kong, Material Security, Netlify, Orbit, Pindrop Security, Preset, RapidAPI, Rasa, Tackle, Tecton, and Yubico.Links: Yet Another Infra Group Discord Server: https://discord.gg/f3xnJzwbeQ “The Cost of Cloud, a Trillion Dollar Paradox” - https://a16z.com/2021/05/27/cost-of-cloud-paradox-market-cap-cloud-lifecycle-scale-growth-repatriation-optimization/ TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: This episode is sponsored in part by Honeycomb. When production is running slow, it's hard to know where problems originate. Is it your application code, users, or the underlying systems? I've got five bucks on DNS, personally. Why scroll through endless dashboards while dealing with alert floods, going from tool to tool to tool that you employ, guessing at which puzzle pieces matter? Context switching and tool sprawl are slowly killing both your team and your business. You should care more about one of those than the other; which one is up to you. Drop the separate pillars and enter a world of getting one unified understanding of the one thing driving your business: production. With Honeycomb, you guess less and know more. Try it for free at honeycomb.io/screaminginthecloud. Observability: it's more than just hipster monitoring.Corey: This episode is sponsored in part by our friends at Sysdig. Sysdig secures your cloud from source to run. They believe, as do I, that DevOps and security are inextricably linked. If you wanna learn more about how they view this, check out their blog, it's definitely worth the read. To learn more about how they are absolutely getting it right from where I sit, visit Sysdig.com and tell them that I sent you. That's S Y S D I G.com. And my thanks to them for their continued support of this ridiculous nonsense.Corey: Welcome to Screaming in the Cloud. I'm Corey Quinn. I'm joined today by someone who has taken a slightly different approach to being—well, we'll call it cloud skepticism here. Martin Casado is a general partner at Andreessen Horowitz and has been on my radar starting a while back, based upon a piece that he wrote focusing on the costs of cloud and how repatriation is going to grow. You wrote that in conjunction with your colleague, Sarah Wang. Martin, thank you so much for joining me. What got you onto that path?Martin: So, I want to be very clear, just to start with is, I think cloud is the biggest innovation that we've seen in infrastructure, probably ever. It's a core part of the industry. I think it's very important, I think every company's going to be using cloud, so I'm very pro-cloud. I just think the nature of how you use clouds is shifting. And that was the focus.Corey: When you first put out your article in conjunction with your colleague as well, like, I saw it and I have to say that this was the first time I'd really come across any of your work previously. And I have my own biases that I started from, so my opening position on reading it was this is just some jerk who's trying to say something controversial and edgy to get attention. That's my frickin job. Excuse me, sir. And who is this clown?So, I started digging, and what I found really changed my perspective because as mentioned at the start of the show, you are a general partner at Andreessen Horowitz, which means you are a VC. You are definitionally almost the archetype of a VC in that sense. And to me, being a venture capitalist means the most interesting thing about you is that you write a large check consisting of someone else's money. And that's never been particularly interesting.Martin: [laugh].Corey: You kind of cut against that grain and that narrative. You have a master's and a PhD in computer science from Stanford; you started your career at one of the national labs—Laurence Livermore, if memory serves—you wound up starting a business, Nicira, if I'm pronouncing that correctly—Martin: Yeah, yeah, yeah.Corey: That you then sold to VMware in 2012, back at a time when that was a noble outcome, rather than a state of failure because VMware is not exactly what it once was. You ran a $600 million a year business while you were there. Basically, the list of boards that you're on is lengthy enough and notable enough that it sounds almost like you're professionally bored, so I don't—Martin: [laugh].Corey: So, looking at this, it's okay, this is someone who actually knows what he is talking about, not just, “Well, I talked to three people in pitch meetings and I now think I know what is going on in this broader industry.” You pay attention, and you're connected, disturbingly well, to what's going on, to the point where if you see something, it is almost certainly rooted in something that is happening. And it's a big enough market that I don't think any one person can keep their finger on the pulse of everything. So, that's when I started really digging into it, paying attention, and more or less took a lot of what you wrote as there are some theses in here that I want to prove or disprove. And I spent a fair bit of time basically threatening, swindling, and bribing people with infinite cups of coffee in order to start figuring out what is going on.And I am begrudgingly left with no better conclusion than you have a series of points in here that are very challenging to disprove. So, where do you stand today, now that, I guess, the whole rise and fall of the hype around your article on cloud repatriation—which yes, yes, we'll put a link to it in the show notes if people want to go there—but you've talked about this in a lot of different contexts. Having had the conversations that you've had, and I'm sure some very salty arguments with people who have a certain vested interest in you being wrong, do you wind up continuing to stand by the baseline positions that you've laid out, or have they evolved into something more nuanced?Martin: So yeah, I definitely want to point out, so this was work done with Sarah Wang was also at Andreessen Horowitz; she's also a GP. She actually did the majority of the analysis and she's way smarter than I am. [laugh]. And so, I'm just very—feel very lucky to work with her on this. And I want to make sure she gets due credit on this.So, let's talk about the furor. So like, I actually thought that this was kind of interesting and it started a good discussion, but instead, like, [laugh] the amount of, like, response pieces and, like, angry emails I got, and [laugh] like, I mean it just—and I kind of thought to myself, like, “Why are people so upset?” I think there's three reasons. I'm going to go through them very quickly because they're interesting.So, the first one is, like, you're right, like, I'm a VC. I think people see a VC and they're like, oh, lack of credibility, lack of accountability, [laugh], you know, doesn't know what they're doing, broad pattern matcher. And, like, I will say, like, I did not necessarily write this as a VC; I wrote this as somebody that's, like, listen, my PhD is an infrastructure; my company was an infrastructure. It's all data center stuff. I had a $600 million a year data center business that sold infrastructure into data centers. I've worked with all of the above. Like, I've worked with Amazon, I've—Corey: So, you sold three Cisco switches?Martin: [laugh]. That's right.Corey: I remember those days. Those were awesome, but not inexpensive.Martin: [laugh]. That's right. Yeah, so like, you know, I had 15 years. It's kind of a culmination of that experience. So, that was one; I just think that people see VC and they have a reaction.The second one is, I think people still have the first cloud wars fresh in their memories and so they just don't know how to think outside of that. So, a lot of the rebuttals were first cloud war rebuttals. Like, “Well, but internal IT is slow and you can't have the expertise.” But like, they just don't apply to the new world, right? Like, listen, if you're Cloudflare, to say that you can't run, like, a large operation is just silly. If you went to Cloudflare and you're like, “Listen, you can't run your own infrastructure,” like, they'd take out your sucker and pat you on the head. [laugh].Corey: And not for nothing, if you try to run what they're doing on other cloud providers from a pure bandwidth perspective, you don't have a company anymore, regardless of how well funded you are. It's a never-full money pit that just sucks all of the money. And I've talked to a number of very early idea stage companies that aren't really founded yet about trying to do things like CDN-style work or streaming video, and a lot of those questions start off with well, we did some back-of-the-envelope math around AWS data transfer pricing, and if our numbers are right, when we scale, we'll be spending $65,000 on data transfer every minute. What did we get wrong?And it's like, “Oh, yeah, you realize that one thing is per hour not per minute, so slight difference there. But no, you're basically correct. Don't do it.” And yeah, no one pays retail price at that volume, but they're not going to give you a 99.999% discount on these things, so come up with a better plan. Cloudflare's business will not work on AWS, full stop.Martin: Yep, yep. So, I legitimately know, basically, household name public companies that are software companies that anybody listening to this knows the name of these companies, who have product lines who have 0% margins because they're [laugh] basically, like, for every dollar they make, they pay a dollar to Amazon. Like, this is a very real thing, right? And if you go to these companies, these are software infrastructure companies; they've got very talented teams, they know how to build, like, infrastructure. To tell them that like, “Well, you know, you can't build your own infrastructure,” or something is, I mean, it's like telling, like, an expert in the business, they can't do what they do; this is what they do. So, I just think that part of the furor, part of the uproar, was like, I just think people were stuck in this cloud war 1.0 mindset.I think the third thing is, listen, we've got an oligopoly, and they employ a bunch of people, and they've convinced a bunch of people they're right, and it's always hard to change that. And I also think there's just a knee-jerk reaction to these big macro shifts. And it was the same thing we did to software-defined networking. You know, like, my grad school work was trying to change networking to go from hardware to software. I remember giving a talk at Cisco, and I was, like, this kind of like a naive grad student, and they literally yelled at me out of the room. They're like, it'll never work.Corey: They tried to burn you as a witch, as I recall.Martin: [laugh]. And so, your specific question is, like, have our views evolved? But the first one is, I think that this macro downturn really kind of makes the problem more acute. And so, I think the problem is very, very real. And so, I think the question is, “Okay, so what happens?”So, let's say if you're building a new software company, and you have a choice of using, like, one of the Big Three public clouds, but it impacts your margins so much that it depresses your share price, what do you do? And I think that we thought a lot more about what the answers there are. And the ones that I think that we're seeing is, some actually are; companies are building their own infrastructure. Like, very famously MosaicML is building their own infrastructure. Fly.io, -building their own infrastructure.Mighty—you know, Suhail's company—building his own infrastructure. Cloudflare has their own infrastructure. So, I think if you're an infrastructure provider, a very reasonable thing to do is to build your own infrastructure. If you're not a core infrastructure provider, you're not; you can still use somebody's infrastructure that's built at a better cost point.So, for example, if I'm looking at a CDN tier, I'm going to use Fly.io, right? I mean, it's like, it's way cheaper, the multi-region is way better, and so, like, I do think that we're seeing, like, almost verticalized clouds getting built out that address this price point and, like, these new use cases. And I think this is going to start happening more and more now. And we're going to see basically almost the delamination of the cloud into these verticalized clouds.Corey: I think there's also a question of scale, where if you're starting out in the evening tonight, to—I want to build, I don't know Excel as a service or something. Great. You're pretty silly if you're not going to start off with a cloud provider, just because you can get instant access to resources, and if your product catches on, you scale out without having to ever go back and build it as quote-unquote “Enterprise grade,” as opposed to having building it on cheap servers or Raspberry Pis or something floating around. By the time that costs hit a certain point—and what that point is going to depend on your stage of company and lifecycle—you're remiss if you don't at least do an analysis on is this the path we want to continue on for the service that we're offering?And to be clear, the answer to this is almost entirely going to be bounded by the context of your business. I don't believe that companies as a general rule, make ill-reasoned decisions. I think that when we see a decision a company makes, by and large, there's context or constraints that we don't see that inform that. I know, it's fun to dunk on some of the large companies' seemingly inscrutable decisions, but I will say, having had the privilege to talk to an awful lot of execs in an awful lot of places—particularly on this show—I don't find myself encountering a whole lot of people in those roles who I come away with thinking that they're a few fries short of a Happy Meal. They generally are very well reasoned in why they do what they do. It's just a question of where we think the future is going on some level.Martin: Yep. So, I think that's absolutely right. So, to be a little bit more clear on what I think is happening with the cloud, which is I think every company that gets created in tech is going to use the cloud for something, right? They'll use it for development, the website, test, et cetera. And many will have everything in the cloud, right?So, the cloud is here to stay, it's going to continue to grow, it's a very important piece of the ecosystem, it's very important piece of IT. I'm very, very pro cloud; there's a lot of value. But the one area that's under pressure is if your product is SaaS if your product is selling Software as a Service, so then your product is basically infrastructure, now you've got a product cost model that includes the infrastructure itself, right? And if you reduce that, that's going to increase your margin. And so, every company that's doing that should ask the question, like, A, is the Big Three the right one for me?Maybe a verticalized cloud—like for example, whatever Fly or Mosaic or whatever is better because the cost is better. And I know how to, you know, write software and run these things, so I'll use that. They'll make that decision or maybe they'll build their own infrastructure. And I think we're going to see that decision happening more and more, exactly because now software is being offered as a service and they can do that. And I just want to make the point, just because I think it's so important, that the clouds did exactly this to the hardware providers. So, I just want to tell a quick story, just because for me, it's just so interesting. So—Corey: No, please, I was only really paying attention to this market from 2016 or so. There was a lot of the early days that I was using as a customer, but I wasn't paying attention to the overall industry trends. Please, storytime. This is how I learned things. I hang out with smart people and I come away a little bit smarter than when I started.Martin: [laugh]. This is, like, literally my fa—this is why this is one of my favorite topics is what I'm about to tell you, which is, so the clouds have always had this argument, right? The big clouds, three clouds, they're like, “Listen, why would you build your own cloud? Because, like, you don't have the expertise, and it's hard and you don't have economies of scale.” Right?And the answer is you wouldn't unless it impacts your share price, right? If it impacts your share price, then of course you would because it makes economic sense. So, the clouds had that exact same dilemma in 2005, right? So, in 2005, Google and Amazon and Microsoft, they looked at their COGS, they looked like, “Okay, I'm offering a cloud. If I look at the COGS, who am I paying?”And it turns out, there was a bunch of hardware providers that had 30% margins or 70% margins. They're like, “Why am I paying Cisco these big margins? Why am I paying Dell these big margins?” Right? So, they had the exact same dilemma.And all of the arguments that they use now applied then, right? So, the exact same arguments, for example, “AWS, you know nothing about hardware. Why would you build hardware? You don't have the expertise. These guys sell to everybody in the world, you don't have the economies of scale.”So, all of the same arguments applied to them. And yet… and yes because it was part of COGS] that it impacted the share price, they can make the economic argument to actually build hardware teams and build chips. And so, they verticalized, right? And so, it just turns out if the infrastructure becomes parts of COGS, it makes sense to optimize that infrastructure. And I would say, the Big Three's foray into OEMs and hardware is a much, much, much bigger leap than an infrastructure company foraying into building their own infrastructure.Corey: There's a certain startup cost inherent to all these things. And the small version of that we had in every company that we started in a pre-cloud era: renting virtual computers from vendors was a thing, but it was still fraught and challenging and things that we use, then, like, GoGrid no longer exist, for good reason. But the alternative was, “Great, I'm going to start building and seeing if this thing has any traction.” Well, you need to go lease a rack somewhere and buy servers from Dell, and they're going to do the fast expedited option, which means only six short weeks until they show up in the data center and then gets sent away because they weren't expecting to receive them. And you wind up with this entire universe of hell between cross-connects and all the rest.And that's before you can ever get anything in front of customers or users to see what happens. Now, it's a swipe of a credit card away and your evening's experiments round up to 25 cents. That was significant. Having to make these significant tens of thousands of dollars of investment just to launch is no longer true. And I feel like that was a great equalizer in some respects.Martin: Yeah, I think that—Corey: And that cost has been borne by the astonishing level of investment that the cloud providers themselves have made. And that basically means that we don't have to. But it does come at a cost.Martin: I think it's also worth pointing out that it's much easier to stand up your own infrastructure now than it has been in the past, too. And so, I think that there's a gradient here, right? So, if you're building a SaaS app, [laugh] you would be crazy not to use the cloud, you just be absolutely insane, right? Like, what do you know about core infrastructure? You know, what do you know about building a back-end? Like, what do you know about operating these things? Go focus on your SaaS app.Corey: The calluses I used to have from crimping my own Ethernet patch cables in data centers have faded by now. I don't want them to come back. Yeah, we used to know how to do these things. Now, most people in most companies do not have that baseline of experience, for excellent reasons. And I wouldn't wish that on the current generation of engineers, except for the ones I dislike.Martin: However, that is if you're building an application. Almost all of my investments are people that are building infrastructure. [laugh]. They're already doing these hardcore backend things; that's what they do: they sell infrastructure. Would you think, like, someone, like, at Databricks doesn't understand how to run infr—of course it does. I mean, like, or Snowflake or whatever, right?And so, this is a gradient. On the extreme app end, you shouldn't be thinking about infrastructure; just use the cloud. Somewhere in the middle, maybe you start on the cloud, maybe you don't. As you get closer to being a cloud service, of course you're going to build your own infrastructure.Like, for example—listen, I mean, I've been mentioning Fly; I just think it's a great example. I mean, Fly is a next-generation CDN, that you can run compute on, where they build their own infrastructure—it's a great developer experience—and they would just be silly. Like, they couldn't even make the cost model work if they did it on the cloud. So clearly, there's a gradient here, and I just think that you would be remiss and probably negligent if you're selling software not to have this conversation, or at least do the analysis.Corey: This episode is sponsored in part by our friend EnterpriseDB. EnterpriseDB has been powering enterprise applications with PostgreSQL for 15 years. And now EnterpriseDB has you covered wherever you deploy PostgreSQL on-premises, private cloud, and they just announced a fully-managed service on AWS and Azure called BigAnimal, all one word. Don't leave managing your database to your cloud vendor because they're too busy launching another half-dozen managed databases to focus on any one of them that they didn't build themselves. Instead, work with the experts over at EnterpriseDB. They can save you time and money, they can even help you migrate legacy applications—including Oracle—to the cloud. To learn more, try BigAnimal for free. Go to biganimal.com/snark, and tell them Corey sent you.Corey: I think there's also a philosophical shift, where a lot of the customers that I talk to about their AWS bills want to believe something that is often not true. And what they want to believe is that their AWS bill is a function of how many customers they have.Martin: Oh yeah.Corey: In practice, it is much more closely correlated with how many engineers they've hired. And it sounds like a joke, except that it's not. The challenge that you have when you choose to build in a data center is that you have bounds around your growth because there are capacity concerns. You are going to run out of power, cooling, and space to wind up having additional servers installed. In cloud, you have an unbounded growth problem.S3 is infinite storage, and the reason I'm comfortable saying that is that they can add hard drives faster than you can fill them. For all effective purposes, it is infinite amounts of storage. There is no forcing function that forces you to get rid of things. You spin up an instance, the natural state of it in a data center as a virtual machine or a virtual instance, is that it's going to stop working two to three years left on maintain when a raccoon hauls it off into the woods to make a nest or whatever the hell raccoons do. In cloud, you will retire before that instance does is it gets migrated to different underlying hosts, continuing to cost you however many cents per hour every hour until the earth crashes into the sun, or Amazon goes bankrupt.That is the trade-off you're making. There is no forcing function. And it's only money, which is a weird thing to say, but the failure mode of turning something off mistakenly that takes things down, well that's disastrous to your brand and your company. Just leaving it up, well, it's only money. It's never a top-of-mind priority, so it continues to build and continues to build and continues to build until you're really forced to reckon with a much larger problem.It is a form of technical debt, where you've kicked the can down the road until you can no longer kick that can. Then your options are either go ahead and fix it or go back and talk to you folks, and it's time for more money.Martin: Yeah. Or talk to you. [laugh].Corey: There is that.Martin: No seriously, I think everybody should, honestly. I think this is a board-level concern for every compa—I sit on a lot of boards; I see this. And this has organically become a board-level concern. I think it should become a conscious board-level concern of, you know, cloud costs, impact COGS. Any software company has it; it always becomes an issue, and so it should be treated as a first-class problem.And if you're not thinking through your options—and I think by the way, your company is a great option—but if you're not thinking to the options, then you're almost fiduciarily negligent. I think the vast, vast majority of people and vast majority of companies are going to stay on the cloud and just do some basic cost controls and some just basic hygiene and they're fine and, like, this doesn't touch them. But there are a set of companies, particularly those that sell infrastructure, where they may have to get more aggressive. And that ecosystem is now very vibrant, and there's a lot of shifts in it, and I think it's the most exciting place [laugh] in all of IT, like, personally in the industry.Corey: One question I have for you is where do you draw the line around infrastructure companies. I tend to have an evolving view of it myself, where things that are hard and difficult do not become harder with time. It used to require a deep-level engineer with a week to kill to wind up compiling and building a web server. Now, it is evolved and evolved and evolved; it is check a box on a webpage somewhere and you're serving a static website. Managed databases, I used to think, were something that were higher up the stack and not infrastructure. Today, I'd call them pretty clearly infrastructure.Things seem to be continually, I guess, a slipping beneath the waves to borrow an iceberg analogy. And it's only the stuff that you can see that is interesting and differentiated, on some level. I don't know where the industry is going at all, but I continue to think of infrastructure companies as being increasingly broad.Martin: Yeah, yeah, yeah. This is my favorite question. [laugh]. I'm so glad you asked. [laugh].Corey: This was not planned to be clear.Martin: No, no, no. Listen, I am such an infrastructure maximalist. And I've changed my opinion on this so much in the last three years. So, it used to be the case—and infrastructure has a long history of, like, calling the end of infrastructure. Like, every decade has been the end of infrastructure. It's like, you build the primitives and then everything else becomes an app problem, you know?Like, you build a cloud, and then we're done, you know? You build the PC and then we're done. And so, they are even very famous talks where people talk about the end of systems when we've be built everything right then. And I've totally changed my view. So, here's my current view.My current view is, infrastructure is the only, really, differentiation in systems, in all IT, in all software. It's just infrastructure. And the app layer is very important for the business, but the app layer always sits on infrastructure. And the differentiations in app is provided by the infrastructure. And so, the start of value is basically infrastructure.And the design space is so huge, so huge, right? I mean, we've moved from, like, PCs to cloud to data. Now, the cloud is decoupling and moving to the CDN tier. I mean, like, the front-end developers are building stuff in the browser. Like, there's just so much stuff to do that I think the value is always going to accrue to infrastructure.So, in my view, anybody that's improving the app accuracy or performance or correctness with technology is an infrastructure company, right? And the more of that you do, [laugh] the more infrastructure you are. And I think, you know, in 30 years, you and I are going to be old, and we're going to go back on this podcast. We're going to talk and there's going to be a whole bunch of infrastructure companies that are being created that have accrued a lot of value. I'm going to say one more thing, which is so—okay, this is a sneak preview for the people listening to this that nobody else has heard before.So Sarah, and I are back at it again, and—the brilliant Sarah, who did the first piece—and we're doing another study. And the study is if you look at public companies and you look at ones that are app companies versus infrastructure companies, where does the value accrue? And there's way, way more app companies; there's a ton of app companies, but it turns out that infrastructure companies have higher multiples and accrue more value. And that's actually a counter-narrative because people think that the business is the apps, but it just turns out that's where the differentiation is. So, I'm just an infra maximalist. I think you could be an infra person your entire career and it's the place to be. [laugh].Corey: And this is the real value that I see of looking at AWS bills. And our narrative is oh, we come in and we fix the horrifying AWS bill. And the naive pass is, “Oh, you cut the bill and make it lower?” Not always. Our primary focus has been on understanding it because you get a phone-number-looking bill from AWS. Great, you look at it, what's driving the cost? Storage.Okay, great. That doesn't mean anything to the company. They want to know what teams are doing this. What's it going to cost for them to add another thousand monthly active users? What is the increase in cost? How do they wind up identifying their bottlenecks? How do they track and assign portions of their COGS to different aspects of their service? How do they trace the flow of capital for their organization as they're serving their customers?And understanding the bill and knowing what to optimize and what not to becomes increasingly strategic business concern.Martin: Yeah.Corey: That's the fun part. That's the stuff I don't see that software has a good way of answering, just because there's no way to use an API to gain that kind of business context. When I started this place, I thought I was going to be building software. It turns out, there's so many conversations that have to happen as a part of this that cannot be replicated by software. I mean, honestly, my biggest competitor for all this stuff is Microsoft Excel because people want to try and do it themselves internally. And sometimes they do a great job, sometimes they don't, but it's understanding their drivers behind their cost. And I think that is what was often getting lost because the cloud obscures an awful lot of that.Martin: Yeah. I think even just summarize this whole thing pretty quickly, which is, like, I do think that organically, like, cloud cost has become a board-level issue. And I think that the shift that founders and execs should make is to just, like, treat it like a first-class problem upfront. So, what does that mean? Minimally, it means understanding how these things break down—A, to your point—B, there's a number of tools that actually help with onboarding of this stuff. Like, Vantage is one that I'm a fan of; it just provides some visibility.And then the third one is if you're selling Software as a Service, that's your core product or software, and particularly it's a infrastructure, if you don't actually do the analysis on, like, how this impacts your share price for different cloud costs, if you don't do that analysis, I would say your fiduciarily negligent, just because the impact would be so high, especially in this market. And so, I think, listen, these three things are pretty straightforward and I think anybody listening to this should consider them if you're running a company, or you're an executive company.Corey: Let's be clear, this is also the kind of problem that when you're sitting there trying to come up with an idea for a business that you can put on slide decks and then present to people like you, these sounds like the paradise of problems to have. Like, “Wow, we're successful and our business is so complex and scaled out that we don't know where exactly a lot of these cost drivers are coming from.” It's, “Yeah, that sounds amazing.” Like, I remember those early days, back when all I was able to do and spend time on and energy on was just down to the idea of, ohh, I'm getting business cards. That's awesome. That means I've made it as a business person.Spoiler: it did not. Having an aggressive Twitter presence, that's what made me as a business person. But then there's this next step and this next step and this next step and this next step, and eventually, you look around and realize just how overwrought everything you've built is and how untangling it just becomes a bit of a challenge and a hell of a mess. Now, the good part is at that point of success, you can bring people in, like, a CFO and a finance team who can do some deep-level analysis to help identify what COGS is—or in some cases, have some founders, explain what COGS is to you—and understand those structures and how you think about that. But it always feels like it's a trailing problem, not an early problem that people focus on.Martin: I'll tell you the reason. The reason is because this is a very new phenomenon that it's part of COGS. It's literally five years new. And so, we're just catching up. Even now, this discussion isn't what it was when we first wrote the post.Like, now people are pretty educated on, like, “Oh yeah, like, this is really an issue. Oh, yeah. It contributes to COGS. Oh, yeah. Like, our stock price gets hit.” Like, it's so funny to watch, like, the industry mature in real-time. And I think, like, going forward, it's just going to be obvious that this is a board-level issue; it's going to be obvious this is, like, a first-class consideration. But I agree with you. It's like, listen, like, the industry wasn't ready for it because we didn't have public companies. A lot of public companies, like, this is a real issue. I mean really we're talking about the last five, seven years.Corey: It really is neat, just in real time watching how you come up with something that sounds borderline heretical, and in a relatively short period of time, becomes accepted as a large-scale problem, and now it's now it is fallen off of the hype train into, “Yeah, this is something to be aware of.” And people's attention spans have already jumped to the next level and next generation of problem. It feels like this used to take way longer for these cycles, and now everything is so rapid that I almost worry that between the time we're recording this and the time that it publishes in a few weeks, what is going to have happened that makes this conversation irrelevant? I didn't used to have to think like that. Now, I do.Martin: Yeah, yeah, yeah, for sure. Well, just a couple of things. I want to talk about, like, one of the reasons that accelerated this, and then when I think is going forward. So, one of the reasons this was accelerated was just the macro downturn. Like, when we wrote the post, you could make the argument that nobody cares about margins because it's all about growth, right?And so, like—and even then, it still saved a bunch of money, but like, a lot of people were like, “Listen, the only thing that matters is growth.” Now, that's absolutely not the case if you look at public market valuations. I mean, people really care about free cash flow, they really care about profitability, and they really care about margins. And so, it's just really forced the issue. And it also, like, you know, made kind of what we were saying very, very clear.I would say, you know, as far as shifts that are going, I think one of the biggest shifts is for every back-end developer, there's, like, a hundred front-end developers. It's just crazy. And those front-end developers—Corey: A third of a DevOps engineer.Martin: [laugh]. True. I think those front-end developers are getting, like, better tools to build complete apps, right? Like, totally complete apps, right? Like they've got great JavaScript frameworks that coming out all the time.And so, you could argue that actually a secular technology change—which is that developers are now rebuilding apps as kind of front-end applications—is going to pull compute away from the clouds anyways, right? Like if instead of, like, the app being some back-end thing running in AWS, but instead is a front-end thing, you know, running in a browser at the CDN tier, while you're still using the Big Three clouds, it's being used in a very different way. And we may have to think about it again differently. Now, this, again, is a five-year going forward problem, but I do feel like there are big shifts that are even changing the way that we currently think about cloud now. And we'll see.Corey: And if those providers don't keep up and start matching those paradigms, there's going to be an intermediary shim layer of companies that wind up converting their resources and infrastructure into things that suit this new dynamic, and effectively, they're going to become the next version of, I don't know, Level 3, one of those big underlying infrastructure companies that most people have never heard of or have to think about because they're not doing anything that's perceived as interesting.Martin: Yeah, I agree. And I honestly think this is why Cloudflare and Cloudflare work is very interesting. This is why Fly is very interesting. It's a set of companies that are, like, “Hey, listen, like, workloads are moving to the front-end and, you know, you need compute closer to the user and multi-region is really important, et cetera.” So, even as we speak, we're seeing kind of shifts to the way the cloud is moving, which is just exciting. This is why it's, like, listen, infrastructure is everything. And, like, you and I like if we live to be 200, we can do [laugh] a great infrastructure work every year.Corey: I'm terrified, on some level, that I'll still be doing the exact same type of thing in 20 years.Martin: [laugh].Corey: I like solving different problems as we go. I really want to thank you for spending so much time talking to me today. If people want to learn more about what you're up to, slash beg you for other people's money or whatnot, where's the best place for them to find you?Martin: You know, we've got this amazing infrastructure Discord channel. [laugh].Corey: Really? I did not know that.Martin: I love it. It's, like, the best. Yeah, my favorite thing to do is drink coffee and talk about infrastructure. And like, I posted this on Twitter and we've got, like, 600 people. And it's just the best thing. So, that's honestly the best way to have these discussions. Maybe can you put, like, the link in, like, the show notes?Corey: Oh, absolutely. It is already there in the show notes. Check the show notes. Feel free to join the infrastructure Discord. I will be there waiting for you.Martin: Yeah, yeah, yeah. That'll be fantastic.Corey: Thank you so much for being so generous with your time. I appreciate it.Martin: This was great. Likewise, Corey. You're always a class act and I really appreciate that about you.Corey: I do my best. Martin Casado, general partner at Andreessen Horowitz. I'm Cloud Economist Corey Quinn, and this is Screaming in the Cloud. If you've enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you've hated this podcast, please leave a five-star review on your podcast platform of choice along with an angry comment telling me that I got it completely wrong and what check you wrote makes you the most interesting.Announcer: The content here is for informational purposes only and should not be taken as legal, business, tax, or investment advice, or be used to evaluate any investment or security and is not directed at any investors or potential investors in any a16z fund. For more details, please see a16z.com/disclosures.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.Announcer: This has been a HumblePod production. Stay humble.

According to Maxime Beauchemin, CEO & Founder at Preset and Creator of Apache Superset and Apache Airflow, building a thriving company is not so straight-forward. So how did he do it? Choosing the right system and services is key for a successful start, and can help you avoid the chaos of having too many tools spread across multiple teams. Max walks the Bros through his recipe for a smart data-driven company, and the genesis of Airflow, Superset & Presto (with some great tidbits about Airflow's old school marketing approach and how the open source platform took on a life of its own).

According to Maxime Beauchemin, CEO & Founder at Preset and Creator of Apache Superset and Apache Airflow, it's not so straight-forward to understand what you're really getting into and the vastness of the skills that are required in order to build a thriving company.Picking the right system and services is key for a successful start, and can help you avoid the chaos of having too many tools spread across multiple teams.Plus, Max walks the bros through the genesis of Airflow, Superset & Presto, and Airflow's old school marketing approach that won the hearts of developers across the world. And just like the terminator, once the machine takes over, you can't stop.

We're really excited to have Mary Costa with us today. Mary is a photographer based in Southern California and is well known for her colorful style. Today we are chatting with her about finding your own style and not going with the crowd. Mary has so many great tips on how to do that yourself as well as has a special suprise for you all at the end of the episode. Mary Costa's Instagram Mary Costa's Website Mary Costa's Preset with Kindred Dare to Develop Podcast Sponsor – Photovision Don't forget to head on over to photovisionprints.com to claim your free roll of their Signature Process + Scan service using the code DARETODEVELOP . Looking to continue your photography education further? Be sure to check out their full library of photography tips! Photovision Website Photovision Education Blog Photovision Instagram DARE TO DEVELOP INSTAGRAM: https://www.instagram.com/daretodevelop DARE TO DEVELOP SHOW NOTES: https://daretodeveloppodcast.com/episodes ASHLEY'S INSTAGRAM: https://www.instagram.com/ashbaumgartner KRISTINE'S INSTAGRAM: https://www.instagram.com/kristineherman_ Thanks for tuning into Dare to Develop. We hope you enjoyed the episode! Please subscribe and leave us a review.

Show Notes(01:46) Douwe went over formative experiences catching the programming virus at the age of 9, combining high school with freelance web development, and studying Computer Science at Utrecht University in college.(03:55) Douwe shared the story behind founding a startup called Stinngo, which led him to join GitLab in 2015 as employee number 10.(05:29) Douwe provided insights on attributes of exceptional engineering talent, given his time hiring developers and eventually becoming GitLab's first Development Lead.(08:28) Douwe unpacked the evolution of his engineering career at GitLab.(11:11) Douwe discussed the motivation behind the creation of the Meltano project in August 2018 to help GitLab's internal data team address the gaps that prevent them from understanding the effectiveness of business operations.(14:38) Douwe reflected on his decision in 2019 to leave GitLab's engineering organization and join the then 5-people Meltano team full-time.(20:24) Douwe shared the details about Meltano's product development journey from its Version 1 to its pivot.(26:18) Douwe reflected on the mental aspect of being the sole person whom Meltano depended on for a while.(29:20) Douwe explained the positioning of Meltano as an open-source self-hosted platform for running data integration and transformation pipelines.(34:54) Douwe shared details of Meltano's ideal customer profiles.(37:45) Douwe provided a quick tour of the Meltano project, which represents the single source of truth regarding one's ELT pipelines: how data should be integrated and transformed, how the pipelines should be orchestrated, and how the various plugins that make up the pipelines should be configured.(40:39) Douwe unpacked different components of Meltano's product strategy, including Meltano SDK, Meltano Hub, and Meltano Labs.(45:05) Douwe discussed prioritizing Meltano's product roadmap in order to bring DataOps functionality to every step of the entire data lifecycle.(48:53) Douwe shared the story behind spinning Meltano out of GitLab in June 2021 and raising a $4.2M Seed funding round led by GV to bring the benefits of open source data integration and DataOps to a wider audience.(52:19) Douwe provided his thoughts behind open-source contributors in a way that can generate valuable product feedback for Meltano.(55:43) Douwe shared valuable hiring lessons to attract the right people who align with Meltano's values.(59:04) Douwe shared advice to startup CEOs who are experimenting with the remote work culture in our “new-normal” virtual working environments.(01:04:10) Douwe unpacked Meltano's mission and vision as outlined in this blog post.(01:06:40) Closing segment.Douwe's Contact InfoGitLabLinkedInTwitterGitHubWebsiteMeltano's ResourcesWebsite | Twitter | LinkedIn | GitHub | YouTubeMeltano Documentation | Product | DataOpsMeltano SDK | Meltano Hub | Meltano LabsCompany Handbook | Community | Values | CareersMentioned ContentArticlesHey, data teams - We're working on a tool just for you (Aug 2018)To-do zero, inbox zero, calendar zero: I think that means I'm done (Sep 2019)Meltano graduates to Version 1.0 (Oct 2019)Revisiting the Meltano strategy: a return to our roots (May 2020)Why we are building an open-source platform for ELT pipelines (May 2020)Meltano spins out of GitLab, raises seed funding to bring data integration into the DataOps era (June 2021)Meltano: The strategic foundation of the ideal data stack (Oct 2021)Introducing your DataOps platform infrastructure: Our strategy for the future of data (Nov 2021)Our next step for building the infrastructure for your Modern Data Stack (Dec 2021)PeopleMaxime Beauchemin (Founder and CEO of Preset, Creator of Apache Airflow and Apache Superset, Angel Investor in Meltano)Benn Stancil (Chief Analytics Officer at Mode Analytics, Well-Known Substack Writer)The entire team at dbt LabsNotesMy conversation with Douwe was recorded back in November 2021. Since then, many things have happened at Meltano. I'd recommend:Checking out their updated company valuesReading Douwe's article about the DataOps Operating System on The New StackExamining Douwe's blog post about moving Meltano to GitHubLooking over the announcement of Meltano 2.0 and the additional seed fundingAbout the showDatacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing khanhle.1013@gmail.com.Subscribe by searching for Datacast wherever you get podcasts or click one of the links below:Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you're new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Tarush Aggarwal is the Founder and CEO of 5X, the modern data stack as a managed service that enables companies to answer business questions without having to worry about building data infrastructure or bringing in the right data engineering team. Chad talks with Tarush about the modern data stack movement, choosing things that make sense on behalf of their customers, and building a team culture at a company with a fairly large time zone distribution. 5x (https://5x.co/) Follow 5x on Twitter (https://twitter.com/DataWith5x), Facebook (https://www.facebook.com/DataWith5x), Instagram (https://www.instagram.com/datawith5x/), YouTube (https://www.youtube.com/channel/UCyOHdgLesV3FesXXl9-8V_w), or LinkedIn (https://www.linkedin.com/company/datawith5x). Follow Tarush on Twitter (https://twitter.com/tarush) or LinkedIn (https://www.linkedin.com/in/tarushaggarwal/). Follow thoughtbot on Twitter (https://twitter.com/thoughtbot) or LinkedIn (https://www.linkedin.com/company/150727/). Become a Sponsor (https://thoughtbot.com/sponsorship) of Giant Robots! Transcript: CHAD: This is the Giant Robots Smashing Into Other Giant Robots Podcast, where we explore the design, development, and business of great products. I'm your host, Chad Pytel. And with me today is Tarush Aggarwal, the Founder and CEO of 5X, the modern data stack as a managed service that enables companies to answer business questions without having to worry about building data infrastructure or bringing in the right data engineering team. Tarush, thank you for joining me. TARUSH: Chad, thank you so much for having me on the show. Really looking forward to being here and hopefully adding some value for your listeners. CHAD: Yes, I'm sure that they will. I think many companies are either thinking about how they build their data infrastructure or thinking about how they leverage data for their business now. So 5X provides a path for them to do that, and I'd love to dive in. How does 5X, like I said in the intro, enable companies to get started without having to worry about building this infrastructure themselves or this team themselves? TARUSH: Yeah, totally. It's a great question. Just to kind of zoom out for a quick second, the data space has been really hot for a few years now, and there's this area often called the modern data stack, which is really led by a few vendors mainly around this concept of the data warehouse, reporting tools, and modeling, and ingestion. And this is really a new area for the data space, which has really become popular. So you also have, you know, ten years ago, you had Hadoop and Spark, and all of these different data tools, which in general have become less popular, and the modern data stack movement is one of the big movements happening. So at a macro level, we have this new movement. If you zoom in, this movement happens to be one of the most fragmented movements. So what that means is for each different layer, you have different vendors. And so, even if you want to do something today as simple as building dashboards, you have to first ingest this data. In your average company, you've got [inaudible] at different sources. You need to put it in. You need to then store it, you need to model it, and then you can build a dashboard. CHAD: You also need to make all the different choices about which ones you're going to choose at every level. TARUSH: Exactly. At each of these levels, you have multiple billion-dollar companies today competing. So the thing about fragmentation of the space and, you know, I think data along with maybe DevOps and security are probably the most fragmented spaces. The thing about fragmented spaces is that they are great for extremely savvy customers; think of large tech companies who have 100% data teams. But for 90% of businesses, if you want to get value from data, it makes it much harder because you have to sign multiple contracts with these vendors, architecture, set up security. So what 5X very, very fundamentally is doing is we're business-focused. We allow you, you know, in a month or two, you better go to 5x.co and add your credit card, and you will have business analytics out of the box. And we can help you make some of these decisions as to what are the best vendors for your price points, for your use cases and give you an end-to-end platform so that you aren't worrying about signing these bills and sort of setting it up. You're focused on your business outcome and your business use cases. CHAD: Where did...I happen to know, but because I did my research for the episode. [laughs] But you were at WeWork leading data at WeWork, right? TARUSH: Yes. CHAD: So I imagine you faced this problem and saw this problem firsthand, right? TARUSH: You know, I've been fortunate that I've spent my career in the data space. So back in the day at Salesforce and now and most recently at WeWork. And companies like this, in general, are aggressively hiring and aggressively growing these teams. So at WeWork, we had 50 people working on stitching together the platform and finding the best vendors, and being involved in that. So at WeWork, we were really focused on building our own version of the platform. I think what's interesting is ever since I left and especially over the last 24 months, where the sort of startup space has become so active, I'm still getting pinged on LinkedIn like every day or two with companies looking to get started. And over a period of time, you see the trends that everyone is reinventing the wheel. What do I do first? What's the first use case? What infrastructure do I need? How do I set this up? So the idea of this really came less from WeWork, where we had the team and the expertise. It came more from the other 90% of the companies that don't have the resources that WeWork had, at least at that time. CHAD: So what do your customers of 5X typically look like then? Are there particular industries or data needs? Or on the tech side, on the development side, what do their development teams look like interacting with 5X? TARUSH: That's a great question. And again, at a macro level, data is a global phenomenon. It's not industry-specific. Now, different industries have different requirements. So obviously, as a consumer, what you need to collect, the tools and infrastructure you need are quite different from a B2B business. So there is this concept that for each vertical, what stack makes sense, and that's, again, something which we can do. Typically, our customers have found some sort of a product-market fit. They have a business, and now they're looking to go scale the business to get to either entering growth phase, or an optimization phase, or a profitability phase. And in each of these phases, data plays a vital role. So they are at this point where they know that they want to get value from it. They might even have a data team with 4,5,10 people. And they really might have figured out their first use cases and had the basic dashboards. And, inevitably, they come to this question of what now? What do we do now? So that's one large sort of vertical. And then the other one is they want to go do it. They want to go invest in data, but they have no idea how to do it. And in that case, they're looking at us not just the platform, but we also have this concept of on-demand talent. Today, we're interviewing thousands of data engineers a week. We get to hire the top 1%, and we pre-train them on different stacks. And then, companies can integrate these lead engineers at a weekly level or completely on-demand and use that to go build out the dashboards. We have never thought of replacing data teams for companies. But it's really interesting to see that some of the early-stage companies are using our platform and our on-demand talent to literally do end-to-end data as a service. CHAD: So at 5X, you're actually providing those team members, those consulting services? TARUSH: Yeah, so we look at it less from the consultant point of view, you know, a consultant typically you would go, and you have your statement of work, and that's going to be a three-month project, and it might be a fixed price. And sort of inevitably, they're looking to...they don't work with hundreds of thousands of companies, a few of them might, but in general, we work a little bit differently. So we have this concept of on-demand talent. So we have these engineers who we hire, and we pre-train them and essentially build software to basically allow people to add these engineers on top of the platform and sort of use them. So they work in one-week sprint cycles. It's fully on-demand. So you can have a group of engineers for one week and the next week not have that. And typically, consultants don't work in that way. And we don't really do the statements of work, and here's what's going to happen. These engineers are sort of put into these things what we call pods, and pods are three engineers and a product manager. And they operate on these one-week sprints. You can use this end-to-end team or these engineering pods to go build out your use cases, which is similar to what a consultant on the services model does, but we do it in more of a platform-first approach. CHAD: That's really interesting. I've had some guests on before where they talk about doing consulting or doing services on top of the recurring revenue platform that they've built or not doing it because it's not interesting to them or that their investors say like, "Don't get into that TNM business time and materials business. You want to focus on recurring revenue." How have you balanced that in your business? TARUSH: The reality is that it doesn't matter which vendor you are in the modern data stack space. You might be Snowflake, or you might be Tableau, or you might be Fivetran or DBT. These are just some of the popular ones. Each of these vendors is just one small part of the stack. And what that means is that they don't have a services model and [inaudible] investors happy. But in reality, it's because they don't have end-to-end stack exposure; you know, there's no company today which knows what their stack looks like. Snowflake doesn't know what their entire stack looks like. I mean, Snowflake [inaudible] its success in engagement because they just want [inaudible] And what 5X is is, you know, we've had to spin these stacks up from scratch for mid-market companies. You'll be able to map your stack. So you might have a few pieces. We can help you see what's missing. But again, because we have visibility end-to-end, having that services model, if you want to call it, makes a lot of sense because, ultimately, we're focused on adding business value. And no one's doing data for the sake of doing data. And no one is doing it to build a 50-person data team. They're doing it ultimately to enable the business. So given that we have this end-to-end scope, we look at our on-demand talent as a massive value-add of using the 5X platform is that you have this ability to get engineers end-to-end that are pre-trained on the platform. So we like it a lot. And we think it's a competitive advantage for us. CHAD: How opinionated is the 5X stack, the default stack? Can you make a lot of choices within it? Are you using lots of different things? You already mentioned Snowflake, Tableau. So it sounds like you're choosing the things that make sense on behalf of your customers. TARUSH: Yeah, so for launch, we're focused on the core BI stack, which is ingestion, storage, monitoring, reporting, and in this stack, also we have picked the best-in-class vendors so Fivetran, Snowflake, DBT, Preset. In some ways, the usual suspects which you think of as you're looking at the stack. Now our goal and really what we're building is this program called the Certified 5X Program, and that's for vendors. And that program allows us to integrate with different partners and do things like account provisioning, configuration, user management, our billing agreement, workflow setup. And as we integrate with more and more vendors, the idea is to really have a single form for the modern data stack. So, in ingestion, for now, we might be using Fivetran since they're the [inaudible], but the idea is we're also talking to Plausible, and Airbyte, and Stitch, and all of the other vendors. So at some point, we really kind of pick and choose between any of them. So the idea is, again, there could be a set of different stuff for a company, which is extremely budget-conscious, and if you're looking more for enterprise capability to use a different vendor in that same category. So ultimately, we're enabling customer freedom in the next few months. At launch, we'll have a smaller selection. But as we get into Q4 and as we get into the next year, we have the next 10-15 vendors lined up who are going to be part of the certified 5X program, and that allows us to add more and more optionality in terms of existing categories. And then, we also will focus on adding new categories like reverse ETL, or data lineage, or augmented analytics. CHAD: I love the idea of being focused for launch, saying these are the biggest things that we need to hit. How long did it take you to get to launch? When did you start working in earnest on 5X and get to a public launch? TARUSH: We've been working on this since last June. So we're 11 months old now. What we really did initially is go build relationships with these vendors. And the first thing we did is we started off more as a services business where we sort of built this automatic interview process where we were interviewing hundreds of engineers a week and adding these engineers and training them on the platform. We would go set up the platform for the customer in a semi-automatic manner. So we have been operational. We're probably working with 15-20 customers at this point, but we did it in a sort of semi-automated way. And over the last few months, as we understood more and more what their needs are, we are transitioning to a platform-first company instead of a services-first company. CHAD: So that means that you were able to be public and start getting customers fairly early on in your journey. It's only been 11 months since you started. And when did you get your first customer? TARUSH: 11 months ago. CHAD: [laughs] So at what point did you find investors and raise money and start to build a team? TARUSH: We've been fortunate enough that we were producing revenue on day one just looking at the services aspect of the business. So we needed a very tiny fundraise back in October, a very small amount. And now that we're getting closer to the platform launch, we might be announcing something soon. CHAD: What did you take money for if you were revenue-generating? Was there something specific that caused you to take it and that it was for? TARUSH: So if you kind of zoom out again and look at this whole concept of building out, you know, I think if we focused on services and focused on growing that part of the business organically, there's no real need for that. But the idea now is we're having a 20-person platform team, building out these integrations, building up software for even things like board management, hiring. The main task today is sort of engineering. So we raised capital to double down on the platform vision and become a platform first. Mid-Roll Ad: I wanted to tell you all about something I've been working on quietly for the past year or so, and that's AgencyU. AgencyU is a membership-based program where I work one-on-one with a small group of agency founders and leaders toward their business goals. We do one-on-one coaching sessions and also monthly group meetings. We start with goal setting, advice, and problem-solving based on my experiences over the last 18 years of running thoughtbot. As we progress as a group, we all get to know each other more. And many of the AgencyU members are now working on client projects together and even referring work to each other. Whether you're struggling to grow an agency, taking it to the next level and having growing pains, or a solo founder who just needs someone to talk to, in my 18 years of leading and growing thoughtbot, I've seen and learned from a lot of different situations, and I'd be happy to work with you. Learn more and sign up today at thoughtbot.com/agencyu. That's A-G-E-N-C-Y, the letter U. CHAD: So, when it comes to building a team, we're talking today, and you're in Bali. Is that where you spend most of your time now? TARUSH: I wish I could spend more time here. CHAD: [laughs] TARUSH: I'm pretty nomadic, which I really like. And I think we were born in COVID...a fun story; I got stuck in Bali for two years. I came here for vacation, and we were locked up. And it's not the worst place in the world to be stuck, and I felt very lucky that it was not somewhere else. So, in general, we started building the pilot while we were still remote. We have folks in 11 countries now. I spent six months of the year around America. That's where our clients are. About 80% of our business is from American companies today, and then I spend some time in India, where our engineering teams are aggressively growing in the Southeast Asian market. And 5X is a Singapore company. So we spend time in Singapore, and if I have some time, I come back to Bali. But in general, we are pretty nomadic. And I think as part of our culture, and how we attract people, one of our core values is what we call the hammock value where if I can build it or if you can build it while lying on a hammock in some part of the world, we're not interested in going back to an office. CHAD: With a fairly large time zone distribution of the team, how do you build a culture? How do people work together? Are people shifting their hours? Or do you build a culture of working asynchronously? TARUSH: We mostly work asynchronously. In general, the engineering teams are based out of India. So engineers who are working on the platform are in the same time zone. In terms of our pods, what's really cool is today, we hire in South America, we hire in Africa, we hire in Southeast Asia, so three distinct time zones. So you have Europe, you have the Americas, and you have the Asian time zone. And when we assemble these pods, and a pod has got three engineers and a technical project manager, we try and have at least two different time zones in a pod. So at least two of the engineers are in separate time zones, which means that for our customers, they have more around-the-clock support. They have more hours where they can get work done, which is great for productivity. So, what that means on our side is that we're really good at being able to communicate asynchronously. We have all this flexibility, and with that, in terms of accountability, the way we do it is we have daily updates. Again, it's asynchronous, so you can send that here's what you did, you know, [inaudible] by. At the end of the week, we do Loom videos really sharing what you've done. We sort focus a lot on like agenda -- CHAD: And Loom is an asynchronous video sharing. People can record videos and share it with everybody. Is that what Loom is? TARUSH: Yeah, sorry, I should mention. Loom is a great video platform that allows you to screen share, and it's just a really cool screen-sharing tool that we record these asynchronous videos and really ingraining it inside our culture. Everyone at 5X knows the importance of sending these updates and agenda before a call and summaries in a Zoom video. So that's how we are able to do it. CHAD: One of the things that we've not struggled with but dealt with at thoughtbot is we've started hiring all throughout the Americas, all throughout Europe, Middle East, and Africa. And we've got team members all over the place. And we want to treat people as employees and give them full benefits. And a lot of people want to work for a local entity and have employment laws and everything. But it's a challenge to do that. We don't necessarily want to set up entities in every country. So one strategy is contracting, another is to work with an international PEO or employer of record. How have you managed that? TARUSH: We use an international agency which allows us to hire in any country. I'm not sure the name of the platform we're using. Karan, our CFO, would know that. CHAD: [laughs] TARUSH: But it allows us on a macro level to be able to hire in all these countries as employees, you know, ask if you have the stock program. And it's also allowing us to give healthcare benefits and things like that, which we really want to have for everyone. And when it comes to the engineers on our network, at the moment, we're hiring them full-time as contractors, but again, we want to extend benefits to them and really, in some ways, give them that flexibility. Do you want to be inside a local jurisdiction where you can have more healthcare benefits and integrations with local governments, you know, employee programs and things like that? Or do you want to take advantage of our culture and be more nomadic? And these are exciting things which we're sort of figuring out now as we [inaudible] some economies of scale around, you know, having this [inaudible] CHAD: Yeah, that's great. And for what it's worth, that's the route that we've taken as well is to work with an international employer of record who actually employs people locally. And many people don't realize, like, you highlighted health benefits. A lot of countries have national health care. But it's really common, especially in white-collar or tech industry employment there, to augment that with supplemental insurance, which is not very expensive, but it is expected and oftentimes necessary to get the kind of coverage that you want to have. TARUSH: I think the world is changing. We're becoming remote-first as well. And the two areas which I believe it's going to affect the most is number one, employment and number two, education. It's just a no-brainer that more and more companies are going to emerge in this space, making it easier to hire remotely and provide benefits and, in some ways, build that operating system for remote entrepreneurs. So I'm not sure if the tools today are great. I think they solve the problem for now. But I expect there to be a lot of innovation in this space over the next few years. CHAD: Well, and I think that the pandemic has pushed that, accelerated that. There are companies now that existed before, but the scale at which they're able to operate now because so many companies have started to go remote and want to employ people everywhere; it's really driving that growth and investment in that area too. And as a result of that, there's going to be a lot of data [laughs] that these companies generate and need to get a handle on. So maybe they'll become customers of 5X, or maybe they already are. TARUSH: Yeah. If you look in the last ten years, I think the last ten years were all about digital marketing with social and sort of advertising, making it very obvious that if you don't have a web presence, if you don't care about your customers think, and if you don't find ways to attract customers, you're not going to exist. So ten years later and all those companies which didn't set up websites and they didn't figure out customer acquisition online probably don't exist anymore. In the next five years or in the next ten years, a lot of these will get a lot more sophisticated. And certainly, data comes in as a competitive advantage. So if you're not focusing on how a customer is using your product and how you personalize and being able to compare the way of spending money in terms of your lead acquisition and really, really optimize at it, what you'll face is that it will become difficult to compete because your competition is getting more and more sophisticated. So a lot of the investment in this is really predicated on becoming more efficient at these core groups of things like go-to-market strategy, engagement, optimizing internal operations as a way to find efficiencies which is typically what technology has enabled. CHAD: Especially small businesses or businesses that are just getting started, if you don't have experience with that, it can feel really overwhelming. And we talked about how 5X by coming to the table with a stack, with a team that can help do that, that's great. And it helps solve that problem. Say that I'm a founder or a CEO, maybe non-technical, and I really am just getting started, but I have a big need; how do I engage with 5X? What's the best way to think about that? And are there things that I might do as a founder that you would recommend, hey, I recognize you can't do everything, but do this, and you'll avoid some pain later on. TARUSH: We have some customers today who use us pre-product. They don't have a product. They don't have any customers. They have no data. But they use us because when they launch, they want to have the right tracking and visibility and reports and metrics. So I would have never thought someone that [inaudible] 5X. But it kind of makes sense that you want to have the right [inaudible] knowledge. You have pros and cons. I think the pros of it is instilling the data culture from day one. Data acts as a bridge between engineering and the business, Chad. It just connects the products from like the business goals. So there is an upside in bringing this on earlier on and building that and instilling that into your culture. I think the flip side of it is that if you don't have product-market fit, if you're shooting darts and seeing what works. And in general, companies at that point are running more on intuition and trying different things to see what sticks. And having systems in place at that scale, very frankly, could also be unnecessary. And at that point, if you're spending $100, you probably want to spend 80-90 of them on bringing out your product and the design that you've got. And I think they'll want to sign to be able to acquire customers, and that sort of shifts then you see the data spending increase. So again, we're obviously happy to help, and our technical product managers have a lot of experience. They're the ones who have been data leaders that are growing companies and businesses like Uber, WeWork, Alibaba, top tech companies. They've already been data team members, so they've always been part of that growth. So they're good people, the on-demand talent. You have expertise over there from someone who's seen this before. And a few of our early-stage companies leverage these people more and more, but the flipside of it is focusing on actually building a product first. CHAD: I love that. I think that that's great advice. And so I assume that there are people who come and to your team or you start talking with them, and you say, "You're not ready for us yet." TARUSH: Yeah, we sort of have done that. We have told folks, you know, Google this, this, and this, and once you have this in place and you're about to go to market, that's the right time to come engage. But at this point, honestly, it might not be the best time for you to start thinking about [inaudible] CHAD: Focus on improving your user experience, getting new users, making the best product you can. That's really great advice. TARUSH: On the flip side of that, I think the problem, not the problem, I don't know if it's the word. I think the mistake a lot of companies make is that they actually get into it too late. The typical fallacy is that the founders are sitting in this gold mine of data. We're just going to have a data scientist come, and he or she is going to start generating all these insights, and we're going to be a data-driven company. And the reality of everything in life is that things take time. You can have the stack from day one, and you can have amazing engineers. But it takes time for you to really understand what's happening in your business. And initially, your data model that's sort of changing because the understanding of the business is changing. Visibility in your data leads to asking better questions. And with asking better questions, you start changing the mental models of what's happening. It takes three iterations before your data model starts to stabilize. And what that means very, very often is that the founder is expecting in three months that the data is going to have a positive ROI and the output the business is getting from the data team is going to be positive. And that's not really how it works. It takes six to nine months. You'd have reporting in the first month and the first two months. But as you move from reporting to visibility and to actually optimization and using that data as an insight, we think of that as a three-quarter project. So number one, I think companies don't know that, and they expect that it happens much sooner. And number two is also the mindset around I'm looking at data to provide positive ROI within a small duration, which is also, in reality, not how it is. CHAD: Tarush, that's really great advice, and I hope people take it to heart. If folks want to get in touch with you or follow along with you or learn more about 5X, where are all the places that they can do that? TARUSH: So our website is 5x.co. Again, that's 5x.co. You can reach out to me at tarush@5x.co. We're also doing a lot of stuff on YouTube. We're doing a lot of podcasts to educate on the data space. We make weekly videos on different topics on our YouTube channel. I'm sure you can just search for 5X. That's another great way to engage with us. CHAD: Wonderful. You can subscribe to this show and find notes for this episode along with a complete transcript at giantrobots.fm. If you have questions or comments, email us at hosts@giantrobots.fm. And you can find me on Twitter at @cpytel. This podcast is brought to you by thoughtbot and produced and edited by Mandy Moore. Thanks so much for listening and see you next time. ANNOUNCER: This podcast was brought to you by thoughtbot. thoughtbot is your expert design and development partner. Let's make your product and team a success. Special Guest: Tarush Aggarwal.

MLOps Coffee Sessions #104 with the creator of Apache Airflow and Apache Superset Maxime Beauchemin, Future of BI co-hosted by Vishnu Rachakonda. // Abstract // Bio Maxime Beauchemin is the founder and CEO of Preset. Original creator of Apache Superset. Max has worked at the leading edge of data and analytics his entire career, helping shape the discipline in influential roles at data-dependent companies like Yahoo!, Lyft, Airbnb, Facebook, and Ubisoft. // MLOps Jobs board https://mlops.pallet.xyz/jobs MLOps Swag/Merch https://www.printful.com/ // Related Links Website: https://www.rungalileo.io/ Trade-Off: Why Some Things Catch On, and Others book by Kevin Maney: https://www.amazon.com/Trade-Off-Some-Things-Catch-Others/dp/0385525958 --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, blogs, newsletters, and more: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Vishnu on LinkedIn: https://www.linkedin.com/in/vrachakonda/ Connect with Max on LinkedIn: https://www.linkedin.com/in/maximebeauchemin/ Timestamps: [00:00] Introduction to Maxime Beauchemin [01:28] Takeaways [03:42] Paradigm of data warehouse [06:38] Entity-centric data modeling [11:33] Metadata for metadata [14:24] Problem of data organization for a rapidly scaling organization [18:36] Machine Learning tooling as a subset or of its own [22:28] Airflow: The unsung hero of the data scientists [27:15] Analyzing Airflow [30:44] Disrupting the field [34:45] Solutions to the ladder problem of empowering exploratory work and mortals superpowers with data [38:04] What to watch out for when building for data scientists [41:47] Rapid fire questions [51:12] Wrap up

When it comes to sending Newsletters on the Our-Hometown WordPress Platform, one of the most frequent requests we receive is for the ability to create a custom newsletter template that a publisher can reuse time and time again, only needing to make minor edits rather than construct an entire newsletter from scratch. This feature has been absent ever since the introduction of the Drag & Drop Composer, which replaced the old-school plain text and HTML-based newsletter templates -- until now! We are excited to announce that the Newsletter Plugin now includes an option within the Drag & Drop Composer to...Article LinkLet us know your thoughts about this episode by reaching out on Social Media!Facebook: https://www.facebook.com/ourhometownincInstagram: https://www.instagram.com/ourhometownwebpublishing/Twitter: https://twitter.com/ourhometownincLinkedIn: https://www.linkedin.com/company/our-hometown-com/..........Our Hometown Web Publishing is The Last Newspaper CMS & Website You'll Ever Need.  We help you generate revenue, engage with readers, and increase efficiency with Our Hometown's Digital & PrePress CMS features to fit your needs & budget.OHT's Web Publishing Platform is:-Powered with WordPress-Hosted on Amazon Web Services-Integrated with Adobe InDesign & Google Drivehttps://our-hometown.comSubscribe to our YouTube channel: https://www.youtube.com/channel/UCKw6KpKUiQkWldrX2-J1Kag?view_as=subscriberOur-Hometown can be reached via email for comments or questions at: ops@Our-Hometown.com

Help us get to 100 subs so we can roll out some new T-shirt promos https://www.patreon.com/thelongwar Table of Contents 00:00 Opening Jokes 9:30 Would You Rather 16:05 Table Top Market Watch  31:50 Click Bait & How It Works By Kenny 33:40 Set Up To Discussion About Preset Terrain   https://www.twitch.tv/dicecheck Welcome to , a new place for bringing the hobby back to wargaming! A podcast hosted by Rob Baer, Kenny Boucher & Wyatt Turk. Become a Veteran of the Long War!  http://thelongwar.net/

Don't let people tell you "Your DAW doesn't matter"! The great ones give you a competitive edge from templates, mastering, advanced Punch and Roll, audio quality, ease of use, and lower learning curves. Productivity and quality, just two of the reasons to make a great choice.

Highlights from this week's conversation include:Max's career journey and role today (2:56)Hitting the limits of traditional BI (11:06)The most influential technology (14:34)Merging with BI and visualization (17:35)Two thoughts on real-time (21:02)Defining BI (24:53)How many have actually achieved self-serve BI (29:54)How preset.io fits in the BI architecture of today (32:36)How to use preset.io to expose analytics (35:23)The analytics process to power something like embedded (42:45)Opportunities that exist right now in the BI market (44:53)Commoditization in visualizations across business models (47:58)What it felt like to create data tooling (51:34)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we'll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com..

Welcome back to the show. This week, our room is a mess. Including a tribute to Vestax DJ Mixers of the 1990s and 2000s, and a two part demo of a rarely heard Moog 984 Four Channel Matrix Mixer. Watch where you step, our room is a mess! This week's mess is brought to you by Vareschi Mastering. https://www.vareschimastering.com/ — Clean it up!

**Preset is hiring**To find out more about Preset's open roles: https://preset.io/careers/Preset is a data exploration and visualization tool powered by the open-source analytics platform Apache supersets. Episode summary:- Introduction to Preset, and Preset's mission and values (0:00 - 5:50)- Questions for Srini, developer advocate at Preset (5:50 - 8:40)- Questions for Katia, senior marketing manager (8:40 - 10:10)- Wrap up & career advice (10:10 - 11:35)Guests:- Maxime Beauchemin, Founder and CEO at Preset- Srini Kadamati, Developer Advocate and Senior Data Scientist at Preset- Katia Zhivaikina, Senior Marketing Manager at PresetHost:- Laetitia Commanay, Podcast Host at Puck.To find out more about Find Your People and Puck:Find Your People is produced by Puck. Our goal is to make hiring more human by adding audio content to careers pages. We want companies to highlight their open roles in a more innovative way. If you want to find out more about Puck, go to our website: careerpuck.com.Want to be a guest company on our podcast?That's awesome. We're always looking for new companies to host. If you want us to share your story, please email us at demo@careerpuck.com And finally, follow us on social media for more exclusive content:- Instagram: https://www.instagram.com/careerpuck/- LinkedIn: https://www.linkedin.com/company/careerpuck/- Twitter: https://twitter.com/careerpuck

On the podcast this season we're sneak peaking the Beta Round of my first group coaching program, Lead with Magic and sharing insights to the curriculum we'll be teaching our students when they join this cycle. Wouldn't it be nice to have a specific recipe edit for your photos that makes them all look beautiful and consistent?! Today Rosemary talks about how we can help you do this with our Coaching and Content program. You can learn more about Lead With Magic at https://leadwithmagic.artisancreativemedia.agency/ We'd love to hear from you on Instagram! Send me a DM @rosemarywatson and let me know what you think of this episode. You can find all the show notes from Listen + Lattes Podcast on our website at https://rosemarywatsonproductions.com/listen-and-lattes/