Podcast appearances and mentions of bruno aziza

Learn how you can unlock the full potential of AI for business intelligence. Host Keith Townsend is joined by  IBM's Bruno Aziza, Vice President, Data, AI & Analytics Strategy, for Six Five Media In the Booth at IBM TechXchange. The two explore IBM's advancements and strategic visions within the realm of AI and the role of Watsonx in the future of Business Intelligence tools. Their discussion covers: The capabilities and benefits of the WATSONX.AI experience in generative AI and machine learning model building Bruno Aziza's enthusiasm for joining IBM and what he looks forward to achieving The critical role of business intelligence in realizing IBM's overarching AI strategy Predictions on the evolution of AI within business intelligence initiatives Innovations IBM is introducing that aim to transform how clients utilize business intelligence tools  

Unlock the secrets of AI's transformative power with latest episode live from Google Next, where UPS's story takes center stage. Joined by AI trailblazers like Bruno Aziza of CapitalG and Pinaki Mitra from UPS, we delve into how UPS is tackling package theft and reshaping package delivery. This isn't just another discussion; it's a firsthand look at how AI and data analytics converge to solve real-world challenges, improving security and efficiency in the e-commerce landscape.Ever wonder how AI can streamline your business operations? Our panelists, including Sanjeev Mohan of Sanjmo and Alok Pareek from Striim, reveal the nuts and bolts of integrating AI into supply chain processes and the pivotal role of data lifecycle management. From enhancing address validation to offering insights for small and medium enterprises, we uncover the practical benefits of AI and the importance of a meticulous approach to data management. Get ready to be inspired by the parallels drawn between packet delivery and data event observability, and the critical steps for aligning AI with your business strategy.We wrap up by exploring the broad implications of generative AI across industries, with case studies that will alter your perspective on AI's potential. Whether it's summarizing legal documents or mining data for pharmaceutical insights, the versatility of AI is showcased in its full glory. We extend our heartfelt thanks to our live audience and listeners, encouraging you to engage with the innovative ideas shared at Google Cloud Next and reminding you of the importance of robust data foundations in harnessing AI's full potential. Join us for a conversation that promises not just to inform but to transform the way you view the intersection of AI and business.“UPS AI Battle Porch Pirates.” ABC News, Good Morning America. Accessed April 10th, 2024. https://abcnews.go.com/GMA/News/video/ups-ai-battle-porch-pirates-103459177.What's New In Data is a data thought leadership series hosted by John Kutay who leads data and products at Striim. What's New In Data hosts industry practitioners to discuss latest trends, common patterns for real world data patterns, and analytics success stories.

Today, I'm joined by Bruno Aziza, who has an incredible background in data and technology and is a dear friend of mine. He has held previous positions at Google, Oracle, Microsoft, and AtScale. He's currently a Partner at CapitalG, which is Alphabet's independent growth fund. In today's episode, we cover: The importance of starting with first principles. This means defining your set of beliefs, particular identity, and your core center of design for your product.  Why you should be competing at the service level for your customers, not the feature level. The biggest learning from Bruno's time as the Head of Data & Analytics at Google Cloud. How to approach confrontation in the workplace. I'm very excited for you to listen.  And by the way, my book has officially launched!  You can order a copy of Sales Pitch by going to https://www.aprildunford.com/books  — If You Want To Skip Ahead: (00:00) Meet my guest Bruno Aziza (01:50) Transitioning from a big company to a startup (06:59) Bruno's big takeaways from his time at a successful startup (14:20) How Bruno applies the “center of design” concept to his thinking (21:00) Connecting with customer pain points (27:59) Lessons from leading Data & Analytics at Google Cloud (33:01) Handling workplace confrontation (35:24) Why being hyper-realistic is a great way to approach cross-functional meetings  (38:18) Bruno's role at CapitalG — Where To Find Bruno Aziza: LinkedIn: https://www.linkedin.com/in/brunoaziza CarCast: https://tinyurl.com/TheCarCast Where To Find April Dunford: Podcast Website: https://www.positioning.show/  Personal Website: https://www.aprildunford.com/  LinkedIn: https://www.linkedin.com/in/aprildunford/  Instagram: https://www.instagram.com/aprildunford/  Twitter: https://twitter.com/aprildunford — Referenced: CapitalG: https://www.capitalg.com/  AtScale: https://www.atscale.com/ — Production and marketing by https://penname.co/

In episode 806 of CXOTalk, we discuss practical applications of generative AI within the enterprise with Bruno Aziza, who was a distinguished voice at Google before joining CapitalG.The conversation explore the technical aspects, the importance of data quality, and the ethical considerations surrounding generative AI deployment.Be sure to watch episode 806 for a live, nuanced discussion aimed at elevating your strategic roadmap for enterprise AI.The conversation includes these topics:► Understanding Generative AI in the Enterprise: A Deep Dive► The Human-Machine Symbiosis in Generative AI► Trust and Data Quality in Generative AI► Financial Impact and Adoption of Generative AI► Enterprise Trends and Use Cases for Generative AI► Deploying Generative AI: Ethical and Practical Considerations► “Trust and Data Quality are the Competitive Moat”► Data Strategy is the Foundation of Generative AI Strategy► How to Identify Use Cases for Enterprise AI► How to Align Enterprise Architecture and AI Strategy► What Does Data Corruption Mean for Generative AI?► Deploying Generative AI: Ethical and Cultural Considerations► How to Drive Adoption of Generative AI in the Enterprise► Future Prospects: The Evolving Landscape of Generative AI and EnterpriseRead the full transcript: https://www.cxotalk.com/episode/generative-ai-strategy-in-the-enterpriseSubscribe: https://www.cxotalk.comBruno Aziza is a Partner at CapitalG, Alphabet's (parent company of Google) independent growth fund. He is a seasoned operator who specializes in high-growth SaaS and enterprise software. Bruno has led product, marketing, sales and business development teams across all phases of growth, from startups to mid-size companies and Fortune 10 software leaders.Michael Krigsman is an industry analyst and publisher of CXOTalk. For three decades, he has advised enterprise technology companies on market messaging and positioning strategy. He has written over 1,000 blogs on leadership and digital transformation and created almost 1,000 video interviews with the world's top business leaders on these topics. His work has been referenced in the media over 1,000 times and in over 50 books. He has presented and moderated panels at numerous industry events around the world.#enterpriseai #generativeai #cxotalk

What's New in Data – a popular podcast and thought leadership series hosted by John Kutay – did a special live episode at the top of Salesforce Tower in San Francisco. Bruno Aziza from CapitalG, Ridhima Kahn from Dapper Labs, and Sanjeev Mohan of SanjMo (former VP of Data at Gartner)  did a recap of 2023 Google Cloud Next's biggest announcements, how (and why) data teams are adopting GenerativeAI, and gave examples of futuristic consumer experiences such as interacting with AI-generated social media influencers. John Kutay moderated the panel in front of a live audience.Follow our panelists on LinkedIn for more insights!https://www.linkedin.com/in/brunoaziza/https://www.linkedin.com/in/ridhimaah...https://www.linkedin.com/in/sanjmo/What's New In Data is a data thought leadership series hosted by John Kutay who leads data and products at Striim. What's New In Data hosts industry practitioners to discuss latest trends, common patterns for real world data patterns, and analytics success stories.

Bruno Aziza – Head of Data and Analytics at Google Cloud – has a unique expert perspective on the data industry  through his work with data executives and visionaries while managing a broad portfolio of products at Google including  BigQuery, Dataflow, Dataproc, Looker, Data Studio, PubSub, Composer, Data Fusion, Catalog, Dataform, Dataprep and Dataplex. In this episode, Bruno we dive into  topics such as the development (and disappointment) of Data Mesh, how it relates to Data Products, along with how data leaders can transform their organizations by first looking inward and transforming one's self.We also speak to why Chief Data Officers are navigating from 'reactive analytics' to data products that are driven by real-time. Follow Bruno Aziza on Linkedin, Twitter, and Medium.What's New In Data is a data thought leadership series hosted by John Kutay who leads data and products at Striim. What's New In Data hosts industry practitioners to discuss latest trends, common patterns for real world data patterns, and analytics success stories.

#dataanalytics #analytics Watch this important CXOTalk episode for a discussion on data and analytics strategy with Bruno Aziza, Head of Data and Analytics at Google Cloud.Bruno shares insights on the convergence of data and workloads, data products, building trust through governance, and activating real-time data for success in the era of digital transformation.Here is more detail on the topics discussed in this episode:► Convergence of data and workloads► Importance of governance to build trust in data► Activation and real-time data► What are data products► Practical examples of data products► Infrastructure requirements for data products vs. traditional dashboards► Roles and team structure in data science► “Data scientists are lonely”► Data science in small organizations► Data products and digital transformation► Team collaboration in data science► How to build a great data culture► Data quality creates trust and confidence in the data► Steps to build a data and analytics strategySubscribe to the CXOTalk and get notified of upcoming LIVE shows: https://www.cxotalk.com/subscribeWatch more and read the complete transcript: https://www.cxotalk.com/episode/mastering-data-and-analytics-strategy-with-bruno-aziza-head-of-data-and-analytics-at-google-cloudBruno Aziza is the Head of Data and Analytics at Google Cloud. He has helped companies of all sizes: startups, mid-size, and large public companies. He helped launch Alpine Data Labs (bought by Tibco), AppStream (bought by Symantec), SiSense (bought Periscope Data) & AtScale. He was at Business Objects when they went IPO (after acquiring Acta & Crystal Reports, & before SAP bought them for $7B). He was at Microsoft when they turned the Data & Analytics business into a $1B giant.Bruno specializes in high-growth SaaS, enterprise software, everything data, analytics, data science and artificial intelligence. He educated in the US, France, the UK & Germany. Bruno has written 2 books on Data Analytics and Enterprise Performance Management. His allegiance is to the Analytics Community worldwide.

Data Mesh Radio Patreon - get access to interviews well before they are releasedEpisode list and links to all available episode transcripts (most interviews from #32 on) hereProvided as a free resource by DataStax AstraDB; George Trujillo's contact info: email (george.trujillo@datastax.com) and LinkedInTranscript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here. You can download their Data Mesh for Dummies e-book (info gated) here.Bruno's LinkedIn: https://www.linkedin.com/in/brunoaziza/Bruno's Medium: https://medium.com/@brunoazizaBruno's YouTube (Carcast videos): https://www.youtube.com/@brunoazizaIn this episode, Scott interviewed Bruno Aziza, Head of Data and Analytics at Google Cloud.Some key takeaways/thoughts from Bruno's point of view:The end goal of your data strategy should be to reliably and scalably turn data into value. The best way to do that is by creating data products. How you get there might be different but don't lose focus on turning data into value."The number one barrier to your ability to drive value of data is not your technology, it's your people and how you organize your team."Focus on the point of what you are trying to deliver, not the actual output. It's not about delivering a dashboard, it's about creating a sustainable way to explore, share, and consume information/insights, whatever form that takes.!Controversial!: There are 3 phases to getting to data driven; 1) is building a data lake or ocean, 2) is data mesh, and 3) is getting to a data product factory equivalent.It's easy to try to put the cart before the horse in data. Before doing something like data mesh, you have to think how you will develop data as a function in your organization.Understanding the data product manager role and leveraging data product managers well is crucial to building an effective data product strategy and practice. They are your data product CEOs.A CDO's effectiveness depends on if they have a true seat at the exec table - can they create the necessary change - and how many people in the...

Today I'm chatting with Bruno Aziza, Head of Data & Analytics at Google Cloud. Bruno leads a team of outbound product managers in charge of BigQuery, Dataproc, Dataflow and Looker and we dive deep on what Bruno looks for in terms of skills for these leaders. Bruno describes the three patterns of operational alignment he's observed in data product management, as well as why he feels ownership and customer obsession are two of the most important qualities a good product manager can have. Bruno and I also dive into how to effectively abstract the core problem you're solving, as well as how to determine whether a problem might be solved in a better way.    Highlights / Skip to: Bruno introduces himself and explains how he created his “CarCast” podcast (00:45) Bruno describes his role at Google, the product managers he leads, and the specific Google Cloud products in his portfolio (02:36) What Bruno feels are the most important attributes to look for in a good data product manager (03:59) Bruno details how a good product manager focuses on not only the core problem, but how the problem is currently solved and whether or not that's acceptable (07:20) What effective abstracting the problem looks like in Bruno's view and why he positions product management as a way to help users move forward in their career (12:38) Why Bruno sees extracting value from data as the number one pain point for data teams and their respective companies (17:55) Bruno gives his definition of a data product (21:42) The three patterns Bruno has observed of operational alignment when it comes to data product management (27:57) Bruno explains the best practices he's seen for cross-team goal setting and problem-framing (35:30)   Quotes from Today's Episode   “What's happening in the industry is really interesting. For people that are running data teams today and listening to us, the makeup of their teams is starting to look more like what we do [in] product management.” — Bruno Aziza (04:29) “The problem is the problem, so focus on the problem, decompose the problem, look at the frictions that are acceptable, look at the frictions that are not acceptable, and look at how by assembling a solution, you can make it most seamless for the individual to go out and get the job done.” – Bruno Aziza (11:28)   “As a product manager, yes, we're in the business of software, but in fact, I think you're in the career management business. Your job is to make sure that whatever your customer's job is that you're making it so much easier that they, in fact, get so much more done, and by doing so they will get promoted, get the next job.” – Bruno Aziza (15:41)   “I think that is the task of any technology company, of any product manager that's helping these technology companies: don't be building a product that's looking for a problem. Just start with the problem back and solution from that. Just make sure you understand the problem very well.” (19:52)   “If you're a data product manager today, you look at your data estate and you ask yourself, ‘What am I building to save money? When am I building to make money?' If you can do both, that's absolutely awesome. And so, the data product is an asset that has been built repeatedly by a team and generates value out of data.” – Bruno Aziza (23:12)   “[Machine learning is] hard because multiple teams have to work together, right? You got your business analyst over here, you've got your data scientists over there, they're not even the same team. And so, sometimes you're struggling with just the human aspect of it.” (30:30)   “As a data leader, an IT leader, you got to think about those soft ways to accomplish the stuff that's binary, that's the hard [stuff], right? I always joke, the hard stuff is the soft stuff for people like us because we think about data, we think about logic, we think, ‘Okay if it makes sense, it will be implemented.' For most of us, getting stuff done is through people. And people are emotional, how can you express the feeling of achieving that goal in emotional value?” – Bruno Aziza (37:36)   Links As referenced by Bruno, “Good Product Manager/Bad Product Manager”: https://a16z.com/2012/06/15/good-product-managerbad-product-manager/ LinkedIn: https://www.linkedin.com/in/brunoaziza/ Bruno's Medium Article on Competing Against Luck by Clayton M. Christensen: https://brunoaziza.medium.com/competing-against-luck-3daeee1c45d4 The Data CarCast on YouTube:  https://www.youtube.com/playlist?list=PLRXGFo1urN648lrm8NOKXfrCHzvIHeYyw

Debi Cabrera and Stephanie Wong have more great Next content this week as we focus on launches specifically related to data and analytics with guests Bruno Aziza and Maire Newton. We start the episode with a look at current customer trends in data, including tools for increasing efficiency when working with many different types of data. Data governance and security is another area where Bruno sees advances in satisfying customer needs. Maire talks about the steps Google is taking to help customers implement knowledge gained with data, including Looker and new integrations with tools like Looker Studio to easily connect tools for better data access and use. Strategic partnerships with companies like Tableau help accomplish these goals as well. With 21 data and analytics launches at Next, exciting solutions are out there for customers. Bruno and Maire highlight their five favorites, like BigQuery support for unstructured data, allowing analysts working with SQL to do more with more data. To simplify workflows, BigQuery integration with Spark is a new feature that Maire tells us about, and we hear more about BigLake and it's increased format support. Data reaches more people easier now with Connected Sheets available for anyone using Google Workspace, and finally we talk more about Looker. Bruno details the four use cases of business intelligence customers and how Google's suite of data products satisfy their needs for a reasonable price. Bruno Aziza Bruno is head of data and analytics for Google Cloud and leads the outbound product management team. He has more than two decades' of Silicon Valley experience, specializing in scaling businesses, and has written two books on Data Analytics and Enterprise Performance Management. Maire Newton Maire is an Outbound Product Manager at Google Cloud with almost 15 years of experience partnering with organizations to develop data solutions and drive digital transformation. She's passionate about helping customers develop data-driven cultures by using technology to meet users where they are. Cool things of the week Google Cloud Next for data professionals: analytics, databases and business intelligence blog ANA104 How Boeing overcame their on-premises implementation challenges with data & AI site ANA100 What's new in Looker and Data Studio site ANA101 What's new in BigQuery site ANA106 How leading organizations are making open source their super power site Google Cloud Next: top AI and ML sessions blog Interview Building the most open data cloud ecosystem post Data Journeys videos Google Cloud Next ‘22 site Looker site Looker Studio site Tableau site BigLake ste BigQuery site Use the BigQuery connector with Spark docs Connected Sheets docs What's something cool you're working on? Debi is getting married and working on Dataflow Prime. Hosts Stephanie Wong and Debi Cabrera

#DataScience #CustomerExperience Data is central to how companies compete, nurture customer relationships, and develop brand loyalty through end-to-end customer experience.In this environment, data strategy is crucial to business success. But, who should be responsible for the data strategy? Who owns the customer and operational data? What are the appropriate metrics and KPIs for a customer-centric data strategy? And most importantly, how does the data strategy support the underlying business goals?To address these questions and more, we speak with Danielle Crop, Chief Data Officer of Albertsons, and Bruno Aziza, Head of Data and Analytics at Google Cloud. This episode explores how Albertsons, with over $62 billion in revenue and 325,000 employees, uses data across the company to improve operations and deliver better and more personalized products and services to customers.The conversation includes these topics:-- On data collection for customer experience-- On data sources that drive customer insights-- On how to use data science for customer experience and personalization-- On ethical considerations of data in customer experience-- On data science talent and the data team at Albertsons-- On building a data culture-- On using data science to deliver business value-- On aligning data strategy and business strategy-- On the Chief Data Officer role-- On customer experience metrics and measuring data performance-- On using data to deepen customer relationships and customer loyaltyRead the complete transcript: https://www.cxotalk.com/episode/data-strategy-customer-experience-google-albertsonsStay up to date with upcoming episodes: https://www.cxotalk.com/subscribeDanielle Crop is the Senior Vice President and Chief Data Officer at Albertsons and is responsible for building and executing a world-class central data strategy that delivers benefits for the customer regardless of whether they shop in store or on the company's digital platforms. Her work uses machine learning and advanced data science capabilities to enhance performance across Albertson's businesses and markets.Bruno Aziza is Head of Data and Analytics at Google Cloud. He specializes in scaling businesses & turning them into global leaders. He has helped companies of all sizes: startups, mid-size, and large public companies. He helped launch Alpine Data Labs (bought by Tibco), AppStream (bought by Symantec), SiSense (bought Periscope Data) and AtScale. He was at Business Objects when they went IPO (after acquiring Acta and Crystal Reports, and before SAP bought them for $7B). He was at Microsoft when they turned the Data & Analytics business into a $1B giant.

We sit down with Bruno Aziza – Head of Analytics at Google Cloud – To discuss the latest trends in data such as data mesh, data governance, and the real-world value of real-time data. What's New In Data is a data thought leadership series hosted by John Kutay who leads data and products at Striim. What's New In Data hosts industry practitioners to discuss latest trends, common patterns for real world data patterns, and analytics success stories.

On the show this week, Mark Mirchandani and Stephanie Wong share two popular episodes of Bruno Aziza's YouTube series Data Journeys. First up, Bruno talks with Aaron Biller of Postmates about their triangle of complex data that includes customer, courier, and merchant. He details their data storage and analytics structure, describing it as a reverse pyramid of tons of data with few engineers to manage and analyze it. To handle this, Postmates takes a stay-out-of-the-way approach by providing good data and letting the analysts do what they do best without micromanaging. Aaron talks about this data architecture, including the use of BigQuery as data lakes to keep data storage simple, and how Google collaboration tools streamline access and authorization tasks. Communication and flexibility are important, Aaron tells us, and he offers other advice for companies designing data systems. Feedback loops, dedicated training, and an open environment with no silos also help foster a productive, healthy data workplace. Matteo of Delivery Hero speaks to Bruno next. With the goal of increasing their global reach and offerings, it's important that Delivery Hero has a smooth data system. Matteo outlines the new data structure they've built to ease onboarding of new companies and territories and describes different use cases for their data. From determining the number of delivery people necessary in each area to offering personalized customer recommendations, Delivery Hero uses Google offerings like Google Analytics and BigQuery to interpret collected data. Matteo details how they tailor data infrastructures for each use case and offers tips to help companies think through their data infrastructure design. Don't work in a bubble, Matteo stresses, and focus on thorough onboarding of team members and clear communication with colleagues and customers. Bruno Aziza Bruno is the Head of Data & Analytics at Google Cloud. He specializes in everything data, from data analytics, to business intelligence, data science, and artificial intelligence. Before working at Google, he worked at companies like Business Objects when it went IPO and Oracle, where his team led a big turnarounds in the business analytics industry. Bruno also had the opportunity to help launch startups like Alpine Data (now part of Tibco). Sisense and AtScale and helped Microsoft grow its Data unit into a $1B business. He has been educated in the US, France, the UK, and Germany and has written two books on Data Analytics and Performance Management. In his spare time, Bruno writes a monthly column on Forbes.com on everything Data, AI and Analytics. Aaron Biller Aaron is the Manager of Data Engineering at Postmates. Matteo Fava Matteo is Senior Director of Global Data Products and Analytics at Delivery Hero. Cool things of the week Celebrating National Muffin Day with machine learning blog Managed Istio-based service mesh on our managed GKE clusters: Anthos Service Mesh comes to GKE Autopilot blog Interview Data Journeys videos Episode 12: How Postmates delivers on data needs with just six data engineers video Episode 5: How Delivery Hero uses data to deliver meals video BigQuery site Google Workspace site Dataproc site Pub/Sub site Google Analytics site Looker site Tableau site Data Studio site GCP Podcast Episode 266: Data Analytics Launches with Bruno Aziza and Eric Schmidt podcast GCP Podcast Episode 281: Google Cloud Next Data, Analytics, and AI Launches with Eric Schmidt and Bruno Aziza podcast What's something cool you're working on? Steph is working on the next Ask Google Cloud event and she wants your Kubernetes questions! Hosts Mark Mirchandani and Stephanie Wong

Bruno Aziza (Head of Data & Analytics @ Google Cloud) joins us to chat about the Data Mesh, Data Fabric, and much more! Streamed live on YouTube and LinkedIn. #datamesh #datafabric #dataengineering --------------------------------- TERNARY DATA We are Matt and Joe, and we're "recovering data scientists". Together, we run a data architecture company called Ternary Data. Ternary Data is not your typical data consultancy. Get no-nonsense, no BS data engineering strategy, coaching, and advice. Trusted by great companies, both huge and small. Subscribe to our newsletter, or check out our services at Ternary Data Site - https://ternarydata.com Please follow our LinkedIn page - https://www.linkedin.com/company/ternary-data/ Subscribe to our YouTube and smash the like button! - https://www.youtube.com/channel/UC3H60XHMp6BrUzR5eUZDyZg Thanks for your support!

At the end of every year, you're probably asking the same questions we are. What are the big changes coming next year? How do I stay ahead of them? And what's separating real trends from the hype?To answer these questions, we are excited to bring together some of the top minds in the industry. In this special episode, we'll pick their brains and dig into what you need to know to thrive in the year ahead. You'll hear from three incredible guests -- all of whom are building and shaping the future of data and analytics:First, Ben Taylor, the Chief AI Evangelist at DataRobotThen, the Global Field CTO of Databricks, Chris D'Agostino.And finally, Bruno Aziza, the Head of Data & Analytics at Google Cloud.Nothing is off the table. So whether you want to hear about augmented everything, dig into the debate around different cloud platforms, or learn why analytics has become more impactful than ever, this is the episode for you.Key TakeawaysCDOs must deliver simplicity but contend with complexity: As the data ecosystem continues to introduce new innovation at an ever increasing rate, data leaders must grapple with all these new capabilities. At the same time, however, the rising need for access to this innovation from nontechnical, business professionals means CDOs must simultaneously deliver simple, intuitive experiences that empower the rest of the businessIs the data warehouse on the way out? D'Agostino makes a bold prediction that within 10 years, the traditional data warehouse won't exist. That begs the question: what will replace it? The lakehouse, data mesh, and data fabric are all contenders, but require organizational changes, not just the introduction of new technologies, as Aziza points out. Preventing bias within models: A consistent problem in the industry - one that we've touched on several times this year - is the potential for machine learning and AI to scale bias in unprecedented ways. As we enter 2022, it will become even more imperative that you and your team are able to answer questions like “how will this model potentially amplify basis,” “how can we prevent biases,” or “what biases exist in our data sets?” Creating an ecosystem of data sharing: The rise of analytics exchanges creates massive opportunity for businesses for two reasons. First, it allows users to share data across platforms at a faster rate. And second, users are now able to share more than just data, but actual assets at an improved rate.In 2022, AI, ML, and data products must prove value: For years, companies have experimented with AI and ML, but as Taylor points out, the disillusionment with the impact of these experiments is at an all time high. So whether you're building data products or launching new AI use cases, data leaders need to lead with the value they will deliver, not only imagine the art of what's possible.--The Data Chief is presented by our friends at ThoughtSpot. Searching through your company's data for insights doesn't have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com.   

Bruno discusses the evolution of the Data Analytics space, its current trends, and shares his view on what lies ahead. BIOBruno Aziza is a recognized authority on Business Intelligence and Information Management. He is a Data & Analytics industry veteran with more than two decades of experience in leading technology companies of various sizes - from startups (Alpine Data) to behemoths (Oracle, Microsoft, and now Google). If you are in the Data & Analytics space be sure to check out:Bruno's book: Drive Business Performance: Enabling a Culture of Intelligent ExecutionBruno's educational series: Data JourneysTIMESTAMPS00:35 Bruno's background02:25 What is Data Analytics 05:40 Evolution of the Data Analytics space07:50 Data Lakes and Data Warehouses 10:10 Crowded Data Analytics space explained12:45 Tailwinds for Data Analytics 14:40 Data Analytics tools in a modern organization16:15 Bruno's Tech Stack17:35 How mature is the Data Analytics space 19:15 Parting thoughts This is the Final Episode of Season A. Make sure to subscribe to be alerted about Season B.

Data and analytics should be a core competence for every Chief Information Officer and Information Technology organization. Given the business, technical, and cultural challenges of using data to make informed business decisions, it's no surprise that data science and analytics are hard.So, how do you make your enterprise data and analytics program a success? Bruno Aziza, head of data and analytics for Google Cloud, explains his approach with valuable lessons based on practical experience.The conversation includes these topics:-- CIO Strategy: How to Lead Enterprise Data and Analytics?-- How to choose a meaningful data problem?-- How important is data infrastructure?-- What is a data mesh?-- How can small organizations take advantage of data and analytics?-- Should the CIO own data and analytics?-- Chief financial officer as the data owner?-- Chief Digital Officer as the data owner?-- Value of low-code and no-code products to CIOs?Bruno Aziza is head of data and analytics for Google Cloud. He specializes in scaling businesses & turning them into global leaders. He helped launch Alpine Data Labs (bought by Tibco), AppStream (bought by Symantec), SiSense (bought Periscope Data) & AtScale. He was at Business Objects when they went IPO (after acquiring Acta & Crystal Reports, & before SAP bought them for $7B). He was at Microsoft when they turned the Data & Analytics business into a $1B giant. Bruno has written 2 books on Data Analytics and Enterprise Performance Management. His allegiance is to the Analytics Community worldwide.Subscribe to the CXOTalk newsletter: https://www.cxotalk.com/subscribeRead the complete transcript: https://www.cxotalk.com/episode/google-cloud-how-manage-enterprise-data-science

In a data-driven world, insights rule the day. The big question is: How? Data Science or Data Warehousing? Python, R or SQL? Embedded or standalone? These are just some of the decisions that today's analytics leaders must answer. Check out this episode of DMRadio to hear host @eric_kavanagh interview several guests, including Bruno Aziza of Google, Eyal David of Model9, and Gael Gioux of Groupe Mutuel.

Want to stay updated on the latest tech trends?Myself and Bruno Aziza will be discussing the latest trends in tech, AI and data science!This will cover everything from the new Ray-Ban smart glasses to the metaverse, as well as the biggest AI and tech trends for 2022, as well as discussions about the latest books we've read, retail trends, and AI ethics.

Inside-out or top-down? Those two options now dominate discussion in the data field, as analytic teams decide whether to embrace a data mesh, or a data fabric. The former is federated, focused on domains of data and a largely self-service approach; the latter leverages the traditional, centralized approach to data management, and a specific information architecture that requires strong organizational leadership. Register for this special edition of DMRadio to hear Host @eric_kavanagh interview Bruno Aziza of Google Cloud, along with Gavin Robertson of WhamTech, and a special guest. They'll discuss the key differences between these two approaches, as well as the technology components that are changing the game, including AI and machine learning, plus automation and augmentation.

Mark Mirchandani is back this week with cohost Bukola Ayodele. We’re talking with Eric Schmidt and Bruno Aziza about all the awesome new analytics, data, and AI launches from last week’s Google Cloud Next conference. Our guests start the show outlining the challenges clients face when storing, organizing, and analyzing data in the cloud. These needs have inspired Google solutions that focus on simplifying data management for customers. Next announcements like BigQuery Omni, which helps customers achieve full data visibility with cross-cloud analytics, and DataPlex, which facilitates data management at scale, will change the way companies think about their data. BigQuery integration with AppSheets and the new Cloud Looker LookML let customers build once and access from anywhere. The new Looker and Tableau integration revolutionizes the use of the semantic model in Tableau, allowing things like company-established data governance and the Looker Blocks ecosystem to pull into Tableau analysis. New Looker Blocks specifically targeted to the healthcare industry were also introduced at Next. We talk about the ML announcements including Vertex AI Workbench, a fully-managed service used for data exploration aimed at simplifying the workloads of data engineers. Serverless Spark on Google Cloud shares these goals by making performance tuning, scaling, infrastructure provisioning, and other tasks fully-managed. The new PostgreSQL interface for Spanner lets clients use tools already developed in PostgreSQL while leveraging the global scaling and other benefits of Spanner. Bruno and Eric share some favorite customer stories as we wrap up this week’s episode. Albertson’s, Renault, and others have interesting data journeys on Google Cloud and our listeners can learn more in the YouTube series hosted by Bruno. Eric Schmidt Eric is the the Head of Advocacy for Data Analytics at Google and has been at Google for almost eight years. Previously, he was with Microsoft, where he led Advocacy and Evangelism there, too. He focuses on products like BigQuery, Dataflow, Dataproc and leads a team of advocates who help customers turn data into value. In his downtime, Eric is a DJ at 90.3 KEXP here in Seattle or online at kexp.org where he focuses on global music culture. You can find Eric on Twitter. His handle is “not that eric” - not to be confused with the ‘other Eric Schmidt' here at Google. In fact, internally, people affectionately call him “cloud E”. Bruno Aziza Bruno is the Head of Data & Analytics at Google Cloud. He specializes in everything data, from data analytics, to business intelligence, data science, and artificial intelligence. Before working at Google, he worked at companies like Business Objects when it went IPO and Oracle, where his team led a big turnarounds in the business analytics industry. Bruno also had the opportunity to help launch startups like Alpine Data (now part of Tibco). Sisense and AtScale and helped Microsoft grow its Data unit into a $1B business. He has been educated in the US, France, the UK, and Germany and has written two books on Data Analytics and Performance Management. In his spare time, Bruno writes a monthly column on Forbes.com on everything Data, AI and Analytics. Cool things of the week Next Reaction: Security and zero-trust announcements blog Next Reaction: New Data Cloud launches blog Next Reaction: Making multicloud easier for all blog Next Reaction: Features to reduce IT carbon emissions and build climate-related solutions blog Next Reaction: Monitor your conversations, get started with CCAI Insights blog Interview GCP Podcast Episode 266: Data Analytics Launches with Bruno Aziza and Eric Schmidt podcast BigQuery site Bringing multi-cloud analytics to your data with BigQuery Omni blog Google Cloud Next—Day 1 livestream - WalMart video Dataplex site AppSheet site Cloud Looker LookML site Tableau site Vertex AI site Vertex AI Workbench site TensorFlow site Apache Spark on Google Cloud site New PostgreSQL Interface makes Cloud Spanner's scalability and availability more open and accessible blog PostgreSQL site Cloud Spanner site Google Earth Engine site Google Maps Platform site Inside Industry Data Management 4.0 at Renault site Chess.com site Google Next Opening Keynote site Data Journeys with Bruno Aziza videos Cloud Next Catalog site Bruno’s Cloud Next Playlist videos Cloud Next Data Analytics Playlist videos Bruno on Linkedin site Lak on Twitter site What’s something cool you’re working on? Bukola is working on the Click to Deploy video series.

Bruno Aziza is a thought leader in Data and Analytics. In this podcast we discussed various key trends and topics influencing the world of data including analyst of the future, value of dark data, user experience, emotions based data storytelling, meaning of Intelligence, and flexibility of data platforms. There are lots of key statistics thrown into this episode which will provide metrics for data leaders and the actions they need to take. Want more? Connect with our host Arvind Murali, Data Chief Strategist at Perficient Learn more about Perficient's Data + Intelligence expertise Connect with our guest: Bruno Aziza | LinkedIn About our guest: Bruno Aziza specializes in scaling businesses and turning them into global leaders. He’s helped companies of all sizes and also helped launch Alpine Data Labs (bought by TIBCO), AppStream (bought by Symantec), SiSense (bought Periscope Data) & AtScale. Bruno specializes in high-growth SaaS, enterprise software, everything data, analytics, data science and artificial intelligence and has written books on data analytics and enterprise performance management. Follow Bruno on Twitter @brunoaziza and LinkedIn, where he shares unbiased insights every Monday. Books: Drive Business Performance, Framers Podcast: Daily Espresso - the economist , Tech Crunch

We look at some of the latest development and unmissable news in the world of technology, artificial intelligence, and data. I am joined by Bruno Aziza from Google.

Stephanie Wong and Jenny Brown are your hosts this week, discussing data analytics with the yin and yang of the field, Bruno Aziza and Eric Schmidt. Our guests introduce us to three new Google offerings, Big Query Omni, Dataplex, and the Analytics Hub, and discuss the uses and implications of each and how they work together to achieve goals. Bruno and Eric describe challenges in data analytics and how Google uses these as opportunities to create problem-solving systems that solve real client problems. Through real-world examples from companies like Equifax, we see how companies are getting more information from their data in a way that creates actionable opportunities to improve customer experiences. For multi-cloud companies, Big Query Omni gets the most out of data that exists in multiple clouds. To accomplish this, Google takes the analytics to the data and is able to reach all appropriate data across clouds without having to move it. This allows for cheaper analysis with much less system downtime. Support for Azure was added this year. The new Dataplex software helps customers intelligently manage data assets, especially in distributed systems. Dataplex lets companies automatically discover data, make data secure without having to move it, and apply governance and policies centrally so the data is accessible. Rather than sit unused, data can now be found easily, analyzed securely, and put to work for companies no matter where their data lives. For analytic asset sharing, Analytics Hub lets companies coordinate with others to get the most use out of their data efficiently. Analytics Hub gets to data value as quickly and easily as possible. Companies can publish, discover, and subscribe to shared assets, create exchanges that combine data sets, and curate exchanges of data and insights for full information sharing. Eric Schmidt Eric is the Head of Advocacy for Data Analytics at Google and has been with us for almost 8 years. He comes to us from Microsoft, where he led Advocacy and Evangelism there, too. Eric is an expert in products like BigQuery, Dataflow, Dataproc and leads a team of leaders who help customers turn data into value. In his downtime, Eric is also a Dj at KEXP 90.3 Seattel - KEPX.ORG where he guest hosts a modern global music show. You can find Eric on Twitter. His handle is @notthateric - not to be confused with the ‘other Eric Schmidt' here at Google. In fact, internally, we affectionately call him “cloude”. Bruno Aziza Bruno is the Head of Data & Analytics at Google Cloud and specializes in everything data, from data analytics, to business intelligence, data science, and artificial intelligence. Before working at Google, Bruno worked at companies like Business Objects when it went IPO and Oracle, where his team led one of the fastest turnarounds in the business analytics industry. He led the launch of startups like Alpine Data (now part of Tibco), Sisense and AtScale and he helped Microsoft grow its Data unit into a $1B business. Bruno has been educated in the US, France, the UK, and Germany. He has written two books on Data Analytics and Performance Management. And he has a monthly column on Forbes.com on everything Data, AI and Analytics. Cool things of the week BigQuery row-level security enables more granular access to data blog Expanding access to quantum today for a better tomorrow blog Expanding partner solutions at the network edge blog Interview Data Cloud Summit site Bringing multi-cloud analytics to your data with BigQuery Omni blog Dataplex site Analytics Hub site Intelligent Data and Analytics Fabric video GCP Podcast Episode 253: Data Governance with Jessi Ashdown and Uri Gilad podcast Public Data Sets site Smart analytics reference patterns site Data and Analytics Sharing at Equifax: Immediate, Interconnected, Scalable, and Secure video BigQuery ML site Learn more about these launches site What’s something cool you’re working on? Jenny has been working on Google Cloud Reader episodes on BigQuery Explained.

Matt and Joe discuss Bruno Aziza's awesome weekly article/video about "What Is Data Engineering?", as well as the Data Engineering Manifesto. Also Listener Q&A. Enjoy! Bruno Aziza blog - https://medium.com/be-data-driven/what-is-data-engineering-fe158db36c1e Data Engineering Manifesto - https://connectingdots.xyz/blog/posts/2021/05/the-data-engineering-manifesto/ --------------------------------- TERNARY DATA We are Matt and Joe, and we're "recovering data scientists". Together, we run a data architecture company called Ternary Data. Ternary Data is not your typical data consultancy. Get no-nonsense, no BS data engineering strategy, coaching, and advice. Trusted by great companies, both huge and small. Ternary Data Site - https://ternarydata.com LinkedIn - https://www.linkedin.com/company/ternary-data/ YouTube - https://www.youtube.com/channel/UC3H60XHMp6BrUzR5eUZDyZg

Thinking it's trendy isn't a strong enough reason to develop a data strategy, culture or structure for your business. You need to integrate the purpose of your business with the purpose of the data you collect and use. We're lucky to be joined by Bruno Aziza, Head of Google Cloud Data & Analytics at Google, who shares how to develop a culture that embraces the use of data in everyday decision-making. What we talked about: - Bruno's dedication and approach to learning and teaching - The evolution of business intelligence - Distilling customers' data challenges - Why you shouldn't let vendors label what you do & instead define it yourself - Red flags that indicate an unsustainable data culture - The difference between data warehouses & data lakes - Actionable advice to build a data-driven culture Check out these resources we mentioned during the podcast: Bruno's LinkedIn profile Drive Business Performance (a book by Bruno) Analytically Yours (Bruno's podcast) Bruno's YouTube channel (where you can access The Car Cast) If you want to hear more, subscribe to Leading with Data on Apple Podcasts, Spotify, or here. Listening on a desktop & can't see the links? Just search for Leading with Data in your favorite podcast player.

Thinking it's trendy isn't a strong enough reason to develop a data strategy, culture or structure for your business. You need to integrate the purpose of your business with the purpose of the data you collect and use. We're lucky to be joined by Bruno Aziza, Head of Google Cloud Data & Analytics at Google, who shares how to develop a culture that embraces the use of data in everyday decision-making. What we talked about: - Bruno's dedication and approach to learning and teaching - The evolution of business intelligence - Distilling customers' data challenges - Why you shouldn't let vendors label what you do & instead define it yourself - Red flags that indicate an unsustainable data culture - The difference between data warehouses & data lakes - Actionable advice to build a data-driven culture Check out these resources we mentioned during the podcast: Bruno's LinkedIn profile Drive Business Performance (a book by Bruno) Analytically Yours (Bruno's podcast) Bruno's YouTube channel (where you can access The Car Cast) If you want to hear more, subscribe to Leading with Data on Apple Podcasts, Spotify, or here. Listening on a desktop & can't see the links? Just search for Leading with Data in your favorite podcast player.

If data has gravity, what does that mean for the cloud? In short, it means the future of data will largely live there, accessed as and when needed by terrestrial and ethereal applications alike! And the best news? There are more options than you can count on two hands. Check out this epsiode of DM Radio to hear from four of the industry's sharpest minds: Bruno Aziza of Google, Stephen Brobst of Teradata, Matt Cusack of Yellowbrick, and Rob Hedgpeth of MariaDB.

In this episode, Bruno Aziza, Head of Data & Analytics at Google Cloud, discusses everything Data & Analytics. From startups to big companies, Bruno has learned a lot along the way and has seen shifts in the field. He discusses those learnings, along with what is coming next. Listen to hear about the importance of his role with the community and going beyond the bytes, the state of Data & Analytics today, the challenges we will face in the near future, and what we can do now. Link to youtube video Link to notes (coming soon) Twitter: @alexasinput other ways to find me --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app Support this podcast: https://anchor.fm/alexagriffith/support

We look at some of the latest development and unmissable news in the world of technology, artificial intelligence, and data. I am joined by Bruno Aziza from Google.

In this episode, we hear from Bruno Aziza, Group Vice President at AI and Data Analytics at Oracle. Aziza encourages his customers to think of the AI acronym not simply as artificial intelligence, but rather as an “applied and invisible” form of augmentation that allows organizations and individuals to get to their end goals faster. Data analysts spend about 80% of their time just preparing data before it can even be analyzed. By applying AI, that time can be cut to nearly nothing, errors can be reduced, and business analysts can reappropriate their time. This allows companies to analyze more efficiently and ask better questions to create a more productive organization. Listen in to hear Aziza share more, including specific examples of company successes. Visit Oracle.com for more information. Aziza also encourages you to learn from customer stories and interviews in his web series, Destination:Insight, on The Oracle Analytics YouTube page.

Mark Rittman is joined by Bruno Aziza, Group Vice President, AI, Data Analytics & Cloud at Oracle to talk about the recently-updated product roadmap for Oracle Analytics, Oracle BI in the marketplace, recent acquisitions in the analytics marketplace and the recent Oracle Analytics Summit at Skywalker Ranch, California.Oracle Analytics SummitOracle Analytics Summit RecapOracle Analytics for Applications: Oracle Analytics Summit Product TourOracle Analytics: Honing 18+ products down to a single brand

Mark Rittman is joined by Bruno Aziza, Group Vice President, AI, Data Analytics & Cloud at Oracle to talk about the recently-updated product roadmap for Oracle Analytics, Oracle BI in the marketplace, recent acquisitions in the analytics marketplace and the recent Oracle Analytics Summit at Skywalker Ranch, California.Oracle Analytics SummitOracle Analytics Summit RecapOracle Analytics for Applications: Oracle Analytics Summit Product TourOracle Analytics: Honing 18+ products down to a single brand

Listen to one of the leading authorities on Business Intelligence (BI), Bruno Aziza, VP Product for Oracle Analytics, as he discusses the top trends dominating the Business Analytics, Data and AI space and why we should pay close attention to these latest developments.