Podcasts about real time analytics

Ben Gamble, Field CTO, VervericaInvestigating the use cases for stream processing technology, such as fraud and anomaly detection; we quantify the value of real-time data analytics for business intelligence and decision-making. Ben Gamble, Field CTO of Ververica talks to Robin Amlôt of IBS Intelligence about the convergence of technologies such as agentic AI and stream processing, and how it can help in the drive towards personalisation.

Alvaro Morales is the cofounder and CEO of Orb, a usage-based billing product for modern software companies. They've raised $44M to date from amazing investors such as Mayfield, Menlo Ventures, and Greylock. Alvaro's favorite book: Conversation in the Cathedral (Author: Mario Vargas Llosa)(00:01) Introduction (00:35) What is Usage-Based Billing?(02:27) Challenges in Metering Usage(04:14) Examples of Consumption-Based Products(05:49) Tools for Usage Metering and Billing(09:08) Founding Story and Validation of Orb(12:11) Building the MVP for a Billing System(14:48) Acquiring the First 10 Customers(18:33) Scaling Sales & Marketing After Initial Traction(21:09) Building the Team & Ideal Candidate Profile(23:26) Technology Stack Behind Orb(25:55) Real-Time Analytics vs Streaming for Billing(27:18) Other Key Components of Orb's Solution(28:38) Why Incumbents Haven't Solved This Problem(31:09) How Orb Uses AI Internally(32:53) Most Exciting AI Advancements for the Future(34:30) Rapid Fire Round--------Where to find Alvaro Morales: LinkedIn: https://www.linkedin.com/in/alvaro-morales/--------Where to find Prateek Joshi: Newsletter: https://prateekjoshi.substack.com Website: https://prateekj.com LinkedIn: https://www.linkedin.com/in/prateek-joshi-infinite X: https://x.com/prateekvjoshi 

Did you know every time you order food, book a ride, or even check who viewed your profile, real-time analytics is powering your experience behind the scenes?In this episode of Great Things with Great Tech, we dive deep into the power of real-time analytics with Kishore Gopalakrishna, CEO and Co-founder of StarTree. StarTree leverages Apache Pinot, a high-performance real-time analytics database, revolutionizing how leading companies like Uber, LinkedIn, Walmart, and Etsy provide instant insights and personalized experiences at massive scale.Kishore shares his journey from a gaming enthusiast fascinated by distributed systems to building mission-critical platforms at Yahoo and LinkedIn, eventually creating Apache Pinot. Discover how StarTree is powering billions of real-time queries per week, enabling businesses to enhance customer interactions, optimize operational decisions, and supercharge modern AI and observability.Key Takeaways: How real-time analytics transform industries, enabling instantaneous insights and rapid decision-making. The evolution from traditional databases to highly efficient columnar, real-time analytics systems. Real-world applications of Apache Pinot, from consumer apps to enterprise observability and operational excellence. How real-time data is accelerating innovations in AI, specifically through Real-Time Retrieval-Augmented Generation (RAG). The future of analytics: seamless data ingestion, enhanced concurrency, and the growing demand for sub-second response times.Links & Resources: Web StarTree: https://startree.ai Kishore Gopalakrishna on LinkedIn: https://www.linkedin.com/in/kgopalak/Apache Pinot: https://pinot.apache.org☑️ Support the Channel: ⁠⁠⁠https://ko-fi.com/gtwgt⁠⁠⁠☑️ Be on #GTwGT: Contact via Twitter @GTwGTPodcast or ⁠⁠visit https://www.gtwgt.com⁠⁠☑️ Subscribe to YouTube: ⁠⁠https://www.youtube.com/@GTwGTPodcast?sub_confirmation=1⁠⁠Check out the full episode on our platforms:Spotify: ⁠⁠https://open.spotify.com/episode/2l9aZpvwhWcdmL0lErpUHC?si=x3YOQw_4Sp-vtdjyroMk3Q⁠⁠Apple Podcasts: ⁠⁠https://podcasts.apple.com/us/podcast/darknet-diaries-with-jack-rhysider-episode-83/id1519439787?i=1000654665731⁠⁠Follow Us:Website: https://gtwgt.comTwitter: https://twitter.com/GTwGTPodcastInstagram: https://instagram.com/GTwGTPodcast☑️ Music: https://www.bensound.com

This episode dives into the transformative world of Microsoft Fabric with Microsoft MVP and "Data God" Chris Wagner. Whether you're a data enthusiast, a business leader, or a technology professional, this episode will give you an insider's look at how Microsoft's latest data platform is reshaping the way organizations manage, analyze, and act on their data.

In today's data-driven world, real-time analytics has become a cornerstone for businesses seeking to make smarter, faster decisions. From enhancing user experiences to enabling continuous intelligence, the ability to process data in real-time is transforming industries. Yet, challenges such as legacy systems and the demand for innovative data management approaches persist.This episode explores the evolution of real-time analytics and its crucial role in modern data processing. We delve into how technology is reshaping the way businesses interact with data and the importance of user-centric design in creating powerful data applications.Joining Christina Stathopoulos, Founder of Dare to Data, is Rahul Rastogi, Chief Innovation Officer at SingleStore. Together, they discuss the necessity of real-time data in today's fast-paced business environment, tackle the challenges organizations face in adapting to this shift, and highlight how data serves as the foundation for AI-driven innovation. Don't miss this insightful discussion packed with practical strategies and forward-looking ideas!Key TakeawaysReal-time analytics has evolved from a luxury to a necessity.Streaming technologies like Kafka and Spark have revolutionized data processing.Legacy systems are often monolithic and ill-suited for real-time analytics.Modern data platforms enable easier data management and integration.Continuous intelligence requires a solid analytics foundation.User experience is critical for the adoption of data applications.Organizations must treat data as a valuable asset.Data governance and quality are essential for effective analytics.The separation of compute from storage enhances scalability.Real-time processing with low latency improves user satisfaction.Chapters00:00 - Introduction to Real-Time Analytics06:14 - The Evolution of Technology in Data Processing10:09 - Challenges of Legacy Systems14:23 - Innovative Approaches to Data Management18:06 - Building a Foundation for AI Innovations21:27 - User Experience in Data Applications

In this episode of ELI, we speak with Eric Fonseca, Co-Founder of IndoAI, a startup building AI-powered edge cameras and computer vision solutions. Inspired by platforms like iOS, Android, and cloud giants such as Azure and AWS, IndoAI is creating an open ecosystem where third-party developers can innovate and contribute their own AI models and applications. The company aims to revolutionize the way enterprises handle attendance, visitor management, security, and more—right at the edge, ensuring data privacy and real-time responsiveness. Eric shares insights into IndoAI's journey, how the COVID-19 pandemic led them to pivot toward advanced face recognition and AI-driven attendance systems, and how they're scaling up to address various use cases like fire detection, intrusion alerts, and vehicle identification. He also discusses the importance of fostering a developer community, the challenges of changing customer mindsets about AI-based solutions, and the path to building a sustainable AI startup. Timestamps/Chapters: 00:00 Introduction 00:03 Meet Eric Fonseca & Genesis of IndoAI 01:22 Transitioning from Face Recognition to a Full AI Camera Platform 02:10 Early Collaboration with Government & Pandemic Pivot 03:33 Edge AI Cameras Explained: On-Device Processing & Data Privacy 05:31 Emphasis on Real-Time Analytics & On-Premise Data Handling 07:32 Use Cases: Visitor Management, Intrusion Detection & Smart Locks 09:16 Evolving from Attendance Apps to AI-Driven Cameras 10:52 The Concept of “Appization”: AI Model Marketplace for Cameras 12:57 Multiple AI Models: Face Recognition, Intrusion, Fire/Smoke Detection 14:23 Market Strategy: B2G, Societies, Corporates, & Channel Partners 16:56 Building a Developer Ecosystem & Revenue Sharing Model 18:16 Enhancing & Improving Models via Hackathons & Collaborations 19:32 Global Trends: Environmental Monitoring & Gesture Recognition in Pharma 21:43 Future Outlook: Starting in India, Expanding Beyond Borders 22:28 Entrepreneurial Lessons: Overcoming Mindset Barriers & Team Alignment 24:26 Defining Entrepreneurship: Persistence, Consistency & Building Legacy

Thu, 12 Dec 2024 23:00:00 +0000 https://mydata.podigee.io/247-new-episode 361bb5940fcb1389efc65eff6f2d0772 Wie etabliert man Datenanalyse in einem traditionellen Fußballverein? Wie geht man mit kulturellen Herausforderungen um? Und was haben FIFA-Spiele mit moderner Performance-Analyse zu tun? Darum geht es in der neuen Folge von MY DATA IS BETTER THAN YOURS, in der Host Jonas Rashedi mit Johannes Riegger von Borussia Mönchengladbach spricht. Als Chief Data Analyst verantwortet er die Entwicklung und Integration von Datenanalyse im Verein. Zunächst geht es im Gespräch um den Aufbau der Dateninfrastruktur bei Borussia. Das Team hat eine komplette Analyseplattform entwickelt - von der Erfassung der Spieldaten bis zur Cloud-Architektur. Johannes leitet dabei ein vierköpfiges Team, das verschiedene Bereiche abdeckt: vom Scouting über die Akademie bis zur Performance-Analyse. Besonders spannend ist der Umgang mit Real-Time-Daten während der Spiele. Durch ein System von Highspeed-Kameras und manueller Erfassung werden Positionsdaten und Ereignisse live verarbeitet. Das Ziel: Verzögerungen von maximal 20-25 Sekunden bei der Datenbereitstellung. Ein wichtiges Thema ist auch der kulturelle Wandel. Johannes erklärt, wie wichtig es ist, die Expertise der Trainer nicht in Frage zu stellen, sondern durch Daten zu unterstützen. Die Bundesliga nimmt dabei eine besondere Position ein - alle Vereine teilen ihre Daten, was einen "sozialistischen" Ansatz in der Datennutzung darstellt. Zum Schluss spricht Johannes über einen besonders innovativen Ansatz: Die Gamification der Performance-Analyse. Inspiriert von FIFA-Spielen werden Leistungsdaten spielerisch aufbereitet - ein Weg, um auch jüngere Spieler für Datenanalyse zu begeistern. MY DATA IS BETTER THAN YOURS ist ein Projekt von BETTER THAN YOURS, der Marke für hochwertige Podcast-Produktionen. Zum LinkedIn-Profil von Johannes: https://www.linkedin.com/in/johannes-riegger-157b77161/ Zur Webseite von Borussia Mönchengladbach: https://www.borussia.de/ Zu allen wichtigen Links rund um Jonas und den Podcast: https://linktr.ee/jonas.rashedi Zeitstempel: 00:00:00 Intro und Begrüßung 00:01:00 Von Freiburg nach Mönchengladbach - Johannes' Weg 00:03:49 Infrastruktur und Datenerfassung im modernen Fußball 00:05:54 Real-Time Analytics 00:15:39 Ansatzpunkte für Analysen 00:17:05 Kulturwandel und Entscheidungsunterstützung 00:26:26 Analyse der Spieler 00:33:57 Operative und organisatorische Umsetzung 00:37:28 Gamification und Performance-Analyse 00:41:00 Persönliche Insights und Abschluss full no

This episode unpacks how AI isn't just about futuristic robotics but is already reshaping industries as unassuming as brooms and brushes. What makes a self-learning system adaptable in such high-stakes settings? Why does it matter that AI “never stops learning”? Join us as we uncover the unexpected depth behind automation and explore how cutting-edge AI is changing MedTech manufacturing from the ground up.

Are likes and follows all that you sought? Think again. Vladimer Botsvadze reveals what personal branding is all about and why you need to build it if you're running an eCommerce business. Discover how to use AI while still showing care efficiently and why emotional intelligence matters the most in any business nowadays.

Want to learn more Postgres? Get on the waiting list for the full course: https://masteringpostgres.com. In this interview, I dive deep with Craig Kerstiens from Crunchy Data into the world of Postgres, covering its rise to prominence, scaling at Heroku, and the power of Postgres extensions. Craig also shares insights on database sharding, the future of Postgres, and why developers love working with it. Follow Craig: Twitter: https://twitter.com/craigkerstiens Crunchy Data Blog: https://www.crunchydata.com/blog Follow Aaron: Twitter: https://twitter.com/aarondfrancis LinkedIn: https://www.linkedin.com/in/aarondfrancis Website: https://aaronfrancis.com - find articles, podcasts, courses, and more. Chapters: 00:00 - Introduction: Welcome to Database School 00:20 - Guest Introduction: Craig Kerstiens and Crunchy Data 01:40 - Craig's Journey from Heroku to Crunchy Data 02:55 - Scaling Postgres at Heroku 04:50 - Mastering Postgres Course Announcement 05:30 - The Importance of Postgres at Heroku 07:50 - The Value of Live SQL with Data Clips 09:25 - Data Clips for Business Intelligence and Real-Time Analytics 11:05 - Heroku's Unique Company Culture and How Data Clips Came to Be 12:30 - Postgres Extensions and Marketplace 14:00 - Citus: Scaling Postgres for Multi-Tenant Applications 15:40 - The Challenges of Sharding in Databases 18:00 - Managing Large Databases and Sharding Keys with Citus 24:00 - The Evolution of Postgres and Its Growing Popularity 31:00 - Postgres for Developers and the Importance of Extensions 35:00 - Extensions as Proving Grounds for Core Postgres Features 37:50 - Building an Extension Marketplace for Postgres 41:00 - Postgres as a Data Platform and Developer Flexibility 46:00 - Why Developers Love Postgres: Stability, Extensions, and Ownership 51:00 - DuckDB: A Fascinating New Database Approach 53:30 - Crunchy Data: What They Offer and Why It Matters 58:30 - Expanding Postgres with DuckDB for Data Warehousing 01:00:00 - Wrapping Up: Where to Find Craig and Crunchy Data

Open source real-time analytics offers unparalleled advantages, providing businesses with freedom and independence to maintain operations seamlessly, even if a vendor issue arises. However, the journey isn't without its challenges. Open source solutions can often be clunky and require specialised expertise to manage effectively. This is where DoubleCloud comes in, offering a managed platform that addresses these obstacles by handling crucial responsibilities such as backups, high availability, and security updates, allowing businesses to focus on leveraging their data.In this podcast, Christina Stathopoulos speaks to Vladimir Borodin, Co-Founder and CEO of DoubleCloud, about open source strategies and the advantages of the DoubleCloud solution. Key Takeaways:DoubleCloud's managed platform helps overcome the challenges of open source, such as clunkiness and a lack of expertise.Successful customer use cases demonstrate the performance and cost benefits of DoubleCloud's solution.The transition phase to DoubleCloud's solution depends on the complexity of the application.Using open source whenever possible is recommended.Chapters:00:00 - Introduction and Background02:29 - The Advantages of Open Source04:21 - Challenges of Open Source06:47 - The Power of Real-Time Analytics09:11 - Success Stories: Improved Performance and Reduced Costs12:54 - Navigating the Transition to DoubleCloud's Solution15:14 - The Importance of Using Open Source

Companies need to provide real time insights to both customers and internal users. These insights power use cases such as personalization and fraud detection. StarTree Cloud is a real-time analytics platform built on Apache Pinot for building such applications that depend on real time insights. In this episode we meet with Chinmay Soman, Head of Product at Startree.ai to discuss the different dimensions of real-time analytics and how Apache Pinot and StarTree Cloud offer a robust platform for providing such insights to applications.AWS Hosts: Nolan Chen & Malini ChatterjeeEmail Your Feedback: rethinkpodcast@amazon.comResources:StarTree:https://startree.aiStarTree community Slack:https://communityinviter.com/apps/startreedata/startree-communityApache Pinot Slack: https://communityinviter.com/apps/apache-pinot/apache-pinotServerless / Free forever workspace:https://stree.ai/free

Real-time data insights help identify performance bottlenecks, manage data efficiently, and drive innovation. Despite the growing need for these capabilities, organisations often face challenges in implementing effective real-time analytics. Achieving high-concurrency data processing is crucial for overcoming performance bottlenecks in real-time analytics. Embracing real-time analytics is not just a necessity, but a way to transform your data into actionable insights, optimise performance, and fuel business growth.Yellowbrick is a modern data platform built on Kubernetes for enterprise data warehousing, ad-hoc and streaming analytics, AI and BI workloads that ensures comprehensive data security, unparalleled flexibility, and high performance. In this podcast, Doug Laney, a Data Strategy Innovation Fellow with West Monroe, speaks to Mark Cusack, the CTO of Yellowbrick, about the power of real-time analytics. Key Takeaways:Real-time analytics enables faster business decisions based on up-to-date data and focuses on enabling actions.Using a SQL data platform like Yellowbrick, designed for high-concurrency data processing, can address performance bottlenecks in real-time analytics.Chapters:00:00 - Introduction and Overview01:07 - The Benefits of Real-Time Analytics06:23 - Overcoming Challenges in Implementing Real-Time Analytics06:51 - High Concurrency Data Processing for Real-Time Analytics13:59 - Yellowbrick: A Secure and Efficient SQL Data Platform

In this video, I talk to Dhruba, CTO @Rockset about search and realtime analytics. We discussed deep internals of Rockset, its architecture and why is it a great fit for search and realtime analytics use cases. Chapters: 00:00 Introduction 02:45 The Evolution of Data Systems: From Hadoop to Rockset 07:30 Understanding Rockset: Real-Time Analytics and Search Defined 12:01 The Technical Edge: Rockset vs. Elasticsearch 18:16 Deep Dive into Rockset's Architecture and Internals 28:21 Partitioning, Hashing, and Data Distribution in Rockset 36:56 Exploring Hot Storage and Cache Layers 37:40 Why Hot Storage is Essential for Low Latency 39:05 Optimizing Data Storage with Compression and Delta Encoding 39:49 Balancing Cost and Performance in Data Storage 41:50 The Power of Converged Indexing in Rockset 45:50 Efficient Query Execution and Index Management 54:51 Leveraging Mutability for Real-Time Analytics 59:24 Deep Dive into Query Processing and Optimization 01:04:21 Understanding Joins and Reporting Queries in Rockset 01:12:23 Future Directions and Vector Search Innovations Index Conference: https://rockset.com/index-conf/ Follow me on Linkedin and Twitter: https://www.linkedin.com/in/kaivalyaapte/ and https://twitter.com/thegeeknarrator If you like this episode, please hit the like button and share it with your network. Also please subscribe if you haven't yet. Database internals series: https://youtu.be/yV_Zp0Mi3xs Popular playlists: Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA- Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17 Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_d Modern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsN Stay Curios! Keep Learning! #rockset #elasticsearch #search #vectorsearch #realtime #databases #sql #joins #indexes

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | Join us for this episode of the Real-Time Analytics podcast where Tim Berglund and Christina Lin from Redpanda discuss the innovative use of WebAssembly for stateless transformations directly within brokers. Learn about the benefits and architecture of this approach, which utilizes unused compute resources for efficient data processing.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | In this episode of the Real-Time Analytics podcast, Tim Berglund explores the innovative architecture of WarpStream with CEO and co-founder Richard Artoul. Discover how WarpStream is transforming the landscape of Kafka with a cloud-native approach that promises operational simplicity, reduced costs, and a stateless data architecture. Richard delves into the technical details of WarpStream, explaining its unique design that separates data and metadata and utilizes object storage for scalability and efficiency.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | Join us for episode #51 of the Real-Time Analytics podcast as our host, Tim Berglund, is joined by Tim Veil, VP of Solutions Engineering and Enablement at StarTree. Dive into an discussion about Testcontainers, a powerful tool that leverages Docker for sophisticated integration testing. Learn how Testcontainers simplifies the testing process against real databases like Apache Pinot, enhancing code reliability and CI pipeline efficiency.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! Join us on the Real-Time Analytics podcast as Tim Berglund sits down with Dr. Rachel Laudan, renowned food historian and author, for a fascinating exploration into the evolution of food delivery and its cultural implications. Dr. Laudan shares her insights on how cooking and food preparation have transformed over centuries, reflecting broader social and economic shifts. This episode promises to deepen your understanding of our culinary past and present, shedding light on the future of meal delivery.

I have Venkat from Rockset back to discuss their search and analytics database built for the cloud, with real-time indexing and full-featured SQL on JSON, time series, geospatial and vector data.

Find out why Bigly's AI scheduler tool can increase your productivity and help you scale your business. Read the new guide today. More details at https://biglysales.com/ai-scheduler-vs-traditional-scheduling-methods/ Bigly Sales, Inc. City: Davie Address: 11197 Blackhawk Blvd. Website: https://biglysales.com/ Phone: +1 561 254 4007 Email: tom@biglysales.com

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In this episode, we continue our conversation with Ujwala Tulshigiri, Engineering Manager at Uber, focusing on the technical intricacies of migrating workloads and technology consolidation. Ujwala provides an in-depth look into Uber's strategic approach to infrastructure decisions, the challenges of technology migration, and how they contribute to and leverage the open-source community. She discusses the complexities of replacing systems like Elasticsearch with alternatives like Pinot, addressing the nuances of data management, search capabilities, and the importance of maintaining low-latency operations.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In this episode of the Real-Time Analytics podcast, host Tim Berglund is joined by Ujwala Tulshigiri, Engineering Manager at Uber, to explore the journey of technology consolidation and the strategic embrace of open-source solutions in challenging economic times. Ujwala offers deep insights into navigating the complexities of technology migration, leveraging the power of the Apache Pinot community, and fostering innovation through collaboration. Tune in to part one of this engaging conversation to learn how Uber optimizes its technology stack for efficiency and scalability.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! Join us for part two of our conversation with Joe Reis, host of 'Monday Morning Data Engineering' and co-author of 'Data Engineering Fundamentals'. In this episode, we continue our exploration of the evolution of data engineering and the shift towards real-time analytics. We discuss the fine line between streaming and real-time processing, the transition from ETL to data engineering, and the significance of immediate data processing in user interactions.

Tim Berglund and Rachel Pedreschi introduce our limited series podcast, Keyboard and Quill, launching in March 2024: https://stree.ai/keyboardandquill Fear not, Tim will continue to host our weekly podcast for data professionals, Real-Time Analytics with Tim Berglund: https://stree.ai/podcastABOUT KEYBOARD AND QUILLKeyboard and Quill is a playful, narrative podcast exploring data and technology through time. Co-hosted by Silicon Valley database startup veterans, Tim Berglund and Rachel Pedreschi, and inspired by the soundscapes of NPR's award-winning Radiolab, Keyboard and Quill is a lively look at how we went from the wheel to the smartphone–from the printing press to the complex data ecosystems powering our modern lives. Tim and Rachel interview academics, philosophers, technologists, thought leaders, cofounders, software engineers, and a variety of other Silicon Valley professionals.

Mike, Seth, & Tommy dive into how important Real Time Analytics and what is going in Microsoft Fabric. Link: https://blog.fabric.microsoft.com/en-us/blog/fabric-changing-the-game-real-time-analytics?ft=All Get in touch: Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page. Visit PowerBI.tips: https://powerbi.tips/ Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitips Subscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVv Subscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎ Check Out Community Jam: https://jam.powerbi.tips Follow Mike: https://www.linkedin.com/in/michaelcarlo/ Follow Seth: https://www.linkedin.com/in/seth-bauer/ Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In this episode of the "Real-Time Analytics" podcast, Tim is joined by Dunith Danushka, a senior developer advocate at Redpanda. They dive into the fascinating world of Redpanda, a cutting-edge streaming technology that's reshaping the realtime analytics ecosystem. Dunith shares his expert knowledge, comparing Redpanda to Kafka, explaining its unique features, and how it operates as an immutable append-only log. They also discuss the technical nuances, including the Seastar framework, and how Redpanda achieves superior performance by working closely with hardware.► https://redpanda.com/blog/redpanda-vs-kafka-performance-benchmark

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! Join host Tim Berglund and StarTree's Peter Corless on the "Real-Time Analytics" podcast as they explore the evolution of data architecture and the relevance of the 'data stack' concept in today's tech landscape. They delve into the shift from traditional structures like the LAMP stack to more dynamic, complex systems, underscoring the need for new frameworks and terminologies. ► LAMP stack: https://en.wikipedia.org/wiki/LAMP_(software_bundle)► JAM stack: https://jamstack.org/► OSI reference model: https://en.wikipedia.org/wiki/OSI_model► Recent Trino episode of podcast: https://youtu.be/_eFdbfn1gO0► The StarTrek Federation: https://memory-alpha.fandom.com/wiki/United_Federation_of_Planets► Look for Peter Corless in StarTree Community Slack (stree.ai/slack)

Access quality data, wherever it resides, with Microsoft Fabric, our next generation managed data and analytics service. Make data accessible across your entire data estate, without having to integrate different sources or work across multiple toolsets. Check out new data mirroring capabilities and AI-powered Copilot experiences, from building data pipelines, to creating predictive models and generating Power BI reports. Microsoft Fabric is a single, fully managed service, that helps you derive quality data from raw fragmented data by using built-in capabilities for data integration, data engineering and data warehousing, as well as for building data science models, real-time analytics, business intelligence, and real-time monitoring and alerts to trigger actions when your data changes. Nellie Gustafsson, Microsoft Fabric's Principal Product Manager, joins Jeremy Chapman to share all the updates.   ► QUICK LINKS: 00:00 - Access quality data across your entire data estate 01:00 - Single, fully managed service 03:18 - Data mirroring 05:29 - Cross-join and query data06:48 - Copilot in Microsoft Fabric 08:06 - Build a machine learning model for predictive insights 09:47 - Use Copilot to generate Power BI reports 11:09 - Wrap up   ► Link References Get information, resources, and sign up for a free trial at https://aka.ms/fabric    ► Unfamiliar with Microsoft Mechanics?  As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft. • Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries • Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog • Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast   ► Keep getting this insider knowledge, join us on social: • Follow us on Twitter: https://twitter.com/MSFTMechanics  • Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/ • Enjoy us on Instagram: https://www.instagram.com/msftmechanics/ • Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In this episode of the 'Real-Time Analytics' podcast, dive into the world of Pinot capacity planning with Sandeep Dabade, a solutions engineer at StarTree. Discover how to calculate the perfect cluster size for your real-time analytics requirements and explore essential technical KPIs like read throughput, write throughput, and data size. Sandeep shares invaluable insights into optimizing Pinot for seamless data processing and analytics, making this episode essential for anyone tackling real-time data challenges.Sandeep's blogs:► https://startree.ai/blog/best-practices-for-designing-tables-in-apache-pinot► https://startree.ai/blog/star-tree-indexes-in-apache-pinot-part-1-understanding-the-impact-on-query-performance► https://startree.ai/blog/star-tree-indexes-in-apache-pinot-part-2-understanding-the-impact-during-high-concurrency► https://startree.ai/blog/star-tree-index-in-apache-pinot-part-3-understanding-the-impact-in-real-customer

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! Join us for Part 2 of the "Real-Time Analytics" podcast featuring Neha Pawar of StarTree, where we delve into Apache Pinot's advanced features including its pluggable architecture, upserts, and Kafka integration. Uncover how Pinot maintains data integrity in real-time analytics and get an insider's look at StarTree Cloud's exclusive tiered storage system.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In this episode of the "Real-Time Analytics" podcast, host Tim and guest Neha Pawar, a founding engineer of StarTree, explore Apache Pinot's unique capabilities in real-time analytics. Neha unpacks Pinot's efficiency, low latency, and high throughput, revealing its prowess in offering real-time insights to end users. Tune in to this first installment of a two-part series for an insightful discussion on the intricacies and innovations that make Pinot a standout in the analytics landscape.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In this episode of the Real-Time Analytics podcast, we welcome Johan Adami, a seasoned software engineer from Stripe, who shares his experience building out Pinot as an internal service for enhanced real-time analytics. Listen in as Johan unveils the journey from the integration of Apache Pinot to tackling the complexities of real-time data processing, offering a first-hand account of the challenges and achievements encountered along the way.

In this episode, we spoke with Dhruba Borthakur, Dhruba is the CTO and Co-founder at Rockset. Rockset is a search and analytics database hosted on the cloud. Dhruba was the founding engineer of the RocksDB project at Facebook and the Principal Architect for HDFS for a while. In this episode, we discuss RocksDB and compare it with LevelDB. We also discuss in detail the Aggregator Leaf Tailer architecture, which started at Facebook and is now powering Rockset. Follow Dhruba: https://twitter.com/dhruba_rocks Follow Alex: https://twitter.com/alexbdebrie

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In this episode of the "Real-Time Analytics" podcast, Tim sits down with Hojjat Jafarpour, a leading figure in the streaming SQL domain. From the early days of KSQL to the cutting-edge work with DeltaStreams, they dive deep into the evolution and impact of real-time analytics, streaming SQL, and cloud-native data solutions. As a former colleague and friend, Hojjat shares his journey and insights on where the streaming world is heading. Join them for an insightful conversation that bridges the past and future of stream processing.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! Discover the secrets behind Wix's cutting-edge real-time analytics in this intriguing episode of the "Real-Time Analytics" podcast. We're joined by Josef Goldstein, Head of R&D for Data Engineering and Analytics Infrastructure at Wix. Tune in to learn how Wix not only uses analytics to make data-driven decisions but also empowers its users to do the same. Uncover the complexities of providing real-time analytics at scale and why it's a game-changer for both Wix and its users.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In this episode of the Real-Time Analytics podcast, host Tim Berglund welcomes Eric Sammer, Founder and CEO of Decodable. Eric, an industry leader in event streaming technology, discusses the company's focus on stream processing, real-time data processing, and integration with systems like Apache Pinot and StarTree. The conversation delves into the challenges and complexities of managing data, from data cleansing to structuring for different use cases. They explore the ideal balance between generalized and specialized systems, emphasizing the importance of flexibility. Ultimately, they highlight how stream processing serves as an effective solution to adjust and distribute data intelligently, providing an essential abstraction point.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In this episode of the Real-Time Analytics podcast, host Tim Berglund discusses the complexities of querying data streams. Tim examines two types of queries - transactional and analytical - and details four methods to handle such inquiries: dumping the data into a data lake, a relational database, using a stream processor, or a real-time analytics database. Each approach has its merits and drawbacks, relating to infrastructure, latency, and the type of analysis required.Robert Zych's tweet: https://twitter.com/zychr/status/1540553490648289280Gunnar Morling's episode: https://youtu.be/cyeKnfdjQlw

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In part two of the "Real-Time Analytics" podcast, Robert Metzger, the PMC chair of Apache Flink, elaborates on using Flink as a developer. Metzger discusses the spectrum of APIs in Flink, ranging from expressive APIs to easy-to-use APIs. He mentions the process function, a low-level, flexible API that exposes basic building blocks of Flink, such as real-time events, state, and event time. Metzger also speaks about the windowing API of Flink and the Async I/O operator. He further details how Flink users can work with a combination of SQL and Java code in the data stream API. You won't want to miss this episode!Flink Deployments At Decodable: https://www.decodable.co/blog/flink-deployments-at-decodable3 Reasons Why You Need Apache Flink for Stream Processing: https://thenewstack.io/3-reasons-why-you-need-apache-flink-for-stream-processing/#:~:text=For%20example%2C%20Uber%20uses%20Flink,streaming%20data%20at%20massive%20scale.

No episódio de hoje, Luan Moreno & Mateus Oliveira entrevistaram André Araújo , atualmente como Field Engineer, Data in Motion na Cloudera.CDP é uma Plataforma de Dados Enterprise Cloudera, com foco na versatilidade em casos de uso como Streaming Platform, possuindo tecnologias como Apache Kafka e Apache Flink .Com CSP, você tem os seguintes benefícios: Apache Kafka - Plataforma de armazenamento de Streaming de Dados líder de mercado;Apache Flink - Plataforma de Processamento de Dados.Neste bate-papo vamos falar sobre:Plataforma de Dados Cloudera ;Plataforma de transmissão Cloudera .O Cloudera sempre foi uma das plataformas mais utilizadas no mercado, agora com a nova versão e casos de uso que atendem diversos cenários, como o caso do CSP ( Cloudera Stream Platform ).André Araújo  = LinkedinCloudera  =  webpage Luan Moreno = https://www.linkedin.com/in/luanmoreno/

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! On today's episode of the Real-Time Analytics podcast, Tim Berglund interviews Oli Makhasoeva, the Director of Developer Relations at Bytewax. Oli, who joined Bytewax as a founding member just six months ago, shares her passion for making data streaming more accessible for Python users. As a data scientist herself, Oli understands the challenges faced when transitioning batch processes to real-time systems. Bytewax, as a Python-native stream processing library, aims to bridge this gap and provide a more convenient and efficient solution for data scientists seeking real-time capabilities. The conversation delves into the benefits of Bytewax's Python-native approach, making it a promising tool for stream processing needs.

On this episode of Embedded Insiders, Dr. Moritz Neukirchner, Head of Software Architecture at Elektrobit, joins us to discuss the business and technology challenges surrounding the growth of software-defined vehicles, and where OEMs and suppliers will generate the most value in automotive in the future.Next on Dev Talk with Rich and Vin, the two are speaking with Stuart Feffer, the co-founder and former CEO of Reality AI. The company was acquired by Renesas in July of 2022, making Stuart the current Head of Real-Time-Analytics at Renesas, and this week Rich and Vin are asking Stuart, “Where do you begin your AI-based design?”But first, the Insiders are discussing their experiences surrounding smart energy and utilities, and power supplies, specifically solar and Gallium Nitride (aka GaN) semiconductors.   Tune In.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! In this episode of the "Real-time Analytics" podcast, Tim Berglund welcomes Olena Kutsenko, a developer advocate with Aiven, to discuss the wonders of Apache Kafka. Tim and Olena reminisce about their early computing days in the '80s (cue nostalgic music), with Olena confessing her love of the ancient programming language, FoxPro. They then dive into Kafka's basics, comparing it to a river of data, except with persistent storage and a knack for real-time analytics. Olena explains how Kafka helps in a microservices world, where communication between modules is crucial, and why it's like having your own personal shop with a delivery system and a recommendation engine. Prepare to be entertained while learning about Kafka's superpower of managing data flow and maintaining order in the chaotic world of distributed systems.

Follow: https://stree.ai/podcast | Sub: https://stree.ai/sub | New episodes every Monday! Mr. Debezium (also known as Gunnar Morling, Software Engineer at Decodable) has been in the business of open source for a long time. While working with Debezium at Red Hat for the better part of a decade, he's seen how all sorts of technologies integrate together and which to use in a variety of use cases. In this episode, Tim talks to Gunnar about his new role at Decodable, if it's really a “Pinot vs Flink” world we're living in, and when to utilize a variety of streaming technologies.ABOUT THE PODCASTFrom StarTree, the original creators of Apache Pinot, "Real-Time Analytics with Tim Berglund" is a podcast dedicated to bringing analytics from the dashboard to the user interface. Accessible but technically rich, the show focuses on the infrastructure, tools, and techniques being developed by the people building the systems that are serving analytics to our users in real-time. New episodes every Monday. Follow on Spotify, Apple, Google, etc at https://stree.ai/podcast

In this episode, we're taking you inside the Game Developers Conference, where our team showcased a custom-built game powered by MongoDB Atlas and MongoDB App Services. You'll hear firsthand experiences from the team who attended the conference, discussing the incredible passion and competitiveness they witnessed from gamers trying to top the leaderboard.We'll dive deep into how MongoDB's real-time analytics and visualizations brought data to life, allowing players to see their own gaming data in action. Plus, you'll get a glimpse into how MongoDB's tech stack made it all possible. Be sure to visit https://mdb.link/gaming for links, resources and more information about MongoDB at Game Developers Conference 2023

Real-time analytics. We've all heard the term, but what does it really mean? It's only fitting that we kick off this podcast with some history and exploration of the term by our host, Tim Berglund (Developer Relations, StarTree).

Nikolay and Michael discuss real-time analytics — what it means, what the options are, and some tips if you're trying to implement it within Postgres. Here are links to a few things we mentioned: Loose index scan / skip scan with recursive CTE (wiki)Zheap (wiki)cstore_fdw (now part of Citus)Timescale compression docsHydra founders interview (on Postgres TV)Materialised views episode pg_ivmTimescale continuous aggregates docsClickhouseSnowflakeReplication episodeTimescale bottomless storage on S3 (blog post)pg_partmanQuerying Postgres from DuckDB (blog post)Heap blog (filter by “Engineering”)Incremental View Maintenance (wiki)PostgreSQL HyperLogLog  Faster counting (by Joe Nelson on the Citus blog)------------------------What did you like or not like? What should we discuss next time? Let us know by tweeting us on @samokhvalov / @michristofides / @PostgresFM, or by commenting on our Google doc.If you would like to share this episode, here's a good link (and thank you!)Postgres FM is brought to you by:Nikolay Samokhvalov, founder of Postgres.aiMichael Christofides, founder of pgMustardWith special thanks to:Jessie Draws for the amazing artwork 

Venkat Venkataramani (CEO & co-founder at Rockset) joins the show to chat about real-time analytics at massive scale. In a former life, Venkat led Facebook's infrastructure team that handled billions of events per second for all of Facebook's user data services. Venkat is on OG in the real-time analytics space, so you'll learn a lot about this topic. #dataengineering #data #realtimedata #analytics

Power Your Real-Time Analytics Without The Headache Using Fivetran's Change Data Capture Integrations

Kishore Gopalakrishna, co-founder and CEO of StarTree, created a solution to a database problem with his co-worker and eventual co-founder Xiang Fu while working at LinkedIn. At the time, LinkedIn was debuting its now-popular feature called Who's Viewed Your Profile, which required the ability to slice and dice massive amounts of data in real time. Kishore and Xiang developed what they called Apache Pinot, a real-time distributed analytical processing data store used to deliver scalable real-time analytics with very low latency. The pair went on to found their open source company, StarTree, in 2019 to build a commercial version of Apache Pinot. The analytics provided by its technology are increasingly essential for all kinds of business decision makers, and the company's quickly emerged as a leader in serving up real-time user-facing analytics at very low latency—for millions. In this episode, Kishore talks about the solutions StarTree provides, its key relationship with the developer community and the roadmap for the company, which just announced a $47 million series B led by GGV, with participation from investor existing investors, Bain and CRV as well as new investor Sapphire Ventures.

Emily Rose Popson is the Head of Demand Generation and Customer Marketing at CallRail. Popson leads the team responsible for driving revenue growth and generating demand for buyer and customer journeys. CallRail assists businesses of all sizes in turning more leads into better customers with leading marketing and sales software. Along with marketing analytics and business communications solutions, CallRail delivers real-time insights for their customers to help them market with confidence.Connect with Emily on LinkedIn: https://www.linkedin.com/in/emilypopsonVisit CallRail's Website: https://www.callrail.com/On This Episode, We Discuss... - What is CallRail?- What is Call-Tracking & What Does it Do?- CallRail's In-Depth Features- Three Key Benefits to Using a Call-Tracking Solution