Date: 2025-11-13. Session illustrée co-animée par l'équipe BI de LVMH Beauty Tech, partageant pratiques, outils et leviers d'adoption de la Self-Service BI. Retours d'expérience terrain, normes internes, outils sur mesure et bonnes pratiques concrètes. Session interactive avec démonstrations et échanges avec le public.

After 1,500+ conversations with CDOs and VPs of data , guest Malcolm Hawker noticed a disturbing pattern: a "limiting mindset" that causes data leaders to fail. He argues that too many leaders blame external factors such as "culture" , "data literacy", or a lack of support rather than taking accountability for delivering value. In this conversation, Malcolm breaks down how this mindset is reinforced by the analyst and consultant community and why it leads to a "value fatigue" where no one can prove their own ROI. He offers a clear path forward, starting with a simple 3-question framework for any new CDO and explains why "culture" is actually an outcome of delivering value, not a prerequisite for it. We also discuss his new book, "The Data Hero Playbook," tackle the "AI Ready" myth , explaining why conflating it with "BI Ready" is holding companies back and why your data is likely "good enough" to start right now.

In this show, we're joined by Sean Chandler, Director of BI at CenterWell Home Health, to explore what it really means to thrive in BI today. Sean shares his personal journey, including his move into teaching, and offers practical insights on building a career in BI, self-learning for advancement, and fostering a strong partnership between BI and data science teams. Whether you're an aspiring BI analyst, a data scientist aiming to improve collaboration, or a career changer eyeing the BI space, this episode is for you. What You'll Learn: How to successfully transition from other roles into BI, and how to know if it's the right fit for you What good collaboration between BI and data science actually looks like, and how to recognize when it's broken How self-taught skills can accelerate your BI career, even without a formal background   🤝 Follow Sean on LinkedIn!   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

Learn best practices and real-world examples for combining dbt, SDLC workflows, AI, and BI to improve analytical accuracy and deliver reliable, conversational insights. This session shows how aligning these tools and methods strengthens data lineage, automates documentation, and empowers true self-service.

Learn how to accelerate and automate migrations with SnowConvert AI, featuring data ecosystem migration agents powered by Snowflake Cortex AI. SnowConvert AI is your free, automated solution designed to dramatically reduce the complexities, costs, and timelines associated with data warehouse and BI migrations. It intelligently analyzes your existing code, automating code conversion, data validation, and streamlining the entire migration process. Join us for an overview of the solution, migration best practices, and live demos.

Seasoned experts Jeroen ter Heerdt, Madzy Stikkelorum, and Marc Lelijveld help you master visual calculations in Power BI for transformative data insights Microsoft Power BI Visual Calculations: Simplifying DAX is a comprehensive guide that demystifies the innovative feature of visual calculations in Power BI. Jeroen, a Principal Product Manager at Microsoft, Madzy, a Data Analytics Consultant, and Marc, a Microsoft Data Platform MVP, bring their extensive expertise to this book, offering you a practical approach to mastering visual calculations. The book is designed to simplify DAX, making it accessible to beginners and empowering you to transform raw data into actionable insights. You will learn to implement visual calculations, understand their benefits, and apply them effectively in real-world scenarios, ultimately enhancing your ability to make data-driven decisions. By reading this book, you will: Understand the fundamentals of visual calculations in Power BI Create your first visual calculation with step-by-step guidance Explore advanced concepts like resetting context in visual calculations Compare visual calculations with other Power BI calculation options Master the performance characteristics of visual calculations Utilize specific functions designed for visual calculations Implement practical use cases like running sums and moving averages Enhance visual calculations with regular DAX expressions Optimize operational processes using data-driven insights Unlock the full potential of Power BI for strategic decision-making About This Book For Power BI users who want to simplify DAX and unlock the full potential of visual calculations without the usual complexities For business executives, managers, and data enthusiasts looking to transform raw data into actionable insights for strategic decision-making

Ryan Dolley, VP of Product Strategy at GoodData and co-host of Super Data Brothers podcast, joined Yuliia and Dumke to discuss the DBT-Fivetran merger and what it signals about the modern data stack's consolidation phase. After 16 years in BI and analytics, Ryan explains why BI adoption has been stuck at 27% for a decade and why simply adding AI chatbots won't solve it. He argues that at large enterprises, purchasing new software is actually the only viable opportunity to change company culture - not because of the features, but because it forces operational pauses and new ways of working. Ryan shares his take that AI will struggle with BI because LLMs are trained to give emotionally satisfying answers rather than accurate ones. Ryan Dolley linkedin

With 700+ monthly BI users, Cribl scales self-service through governance, SDLC workflows, and smart AI practices. Join Priya Gupta and Chris Merrick to see how Git, Omni’s dbt integration, and a $20 auto-doc hack to enrich 100+ models helps deliver fast and trusted AI-powered insights.

Teams across industries spend countless hours every week, month, and quarter creating data-driven slide decks and documents for leadership reviews, business updates, and client reporting—even though the data lives in their BI tools. This “last mile” of data reporting remains highly manual, repetitive, and a drain on strategic bandwidth. In this session, we’ll share how leading companies are automating this process with Rollstack: Sony Music’s The Orchard streamlines leadership business reviews and scales reporting across its network of labels, enabling its lean Analytics team to focus on insights instead of slide production. CarGurus empowers its Customer Success teams to scale client QBR reporting, ensuring consistent, reliable outputs while saving hours of manual work. Join us to see how these organizations are transforming reporting workflows and giving their teams more time to focus on decisions that move the business forward—instead of being stuck as PowerPoint jockeys.

Semantic models promise clarity in analytics, but building them is still a challenge. See how leading data teams auto-generate models from BI metadata—giving data teams consistent definitions, faster validation, and trustworthy context for AI-driven insights.

Learn how to accelerate and automate migrations with SnowConvert AI, featuring data ecosystem migration agents powered by Snowflake Cortex AI. SnowConvert AI is your free, automated solution designed to dramatically reduce the complexities, costs, and timelines associated with data warehouse and BI migrations. It intelligently analyzes your existing code, automating code conversion, data validation, and streamlining the entire migration process.

Summary In this episode of the Data Engineering Podcast, host Tobias Macey welcomes back Nick Schrock, CTO and founder of Dagster Labs, to discuss Compass - a Slack-native, agentic analytics system designed to keep data teams connected with business stakeholders. Nick shares his journey from initial skepticism to embracing agentic AI as model and application advancements made it practical for governed workflows, and explores how Compass redefines the relationship between data teams and stakeholders by shifting analysts into steward roles, capturing and governing context, and integrating with Slack where collaboration already happens. The conversation covers organizational observability through Compass's conversational system of record, cost control strategies, and the implications of agentic collaboration on Conway's Law, as well as what's next for Compass and Nick's optimistic views on AI-accelerated software engineering.

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data managementData teams everywhere face the same problem: they're forcing ML models, streaming data, and real-time processing through orchestration tools built for simple ETL. The result? Inflexible infrastructure that can't adapt to different workloads. That's why Cash App and Cisco rely on Prefect. Cash App's fraud detection team got what they needed - flexible compute options, isolated environments for custom packages, and seamless data exchange between workflows. Each model runs on the right infrastructure, whether that's high-memory machines or distributed compute. Orchestration is the foundation that determines whether your data team ships or struggles. ETL, ML model training, AI Engineering, Streaming - Prefect runs it all from ingestion to activation in one platform. Whoop and 1Password also trust Prefect for their data operations. If these industry leaders use Prefect for critical workflows, see what it can do for you at dataengineeringpodcast.com/prefect.Data migrations are brutal. They drag on for months—sometimes years—burning through resources and crushing team morale. Datafold's AI-powered Migration Agent changes all that. Their unique combination of AI code translation and automated data validation has helped companies complete migrations up to 10 times faster than manual approaches. And they're so confident in their solution, they'll actually guarantee your timeline in writing. Ready to turn your year-long migration into weeks? Visit dataengineeringpodcast.com/datafold today for the details. Your host is Tobias Macey and today I'm interviewing Nick Schrock about building an AI analyst that keeps data teams in the loopInterview IntroductionHow did you get involved in the area of data management?Can you describe what Compass is and the story behind it?context repository structurehow to keep it relevant/avoid sprawl/duplicationproviding guardrailshow does a tool like Compass help provide feedback/insights back to the data teams?preparing the data warehouse for effective introspection by the AILLM selectioncost managementcaching/materializing ad-hoc queriesWhy Slack and enterprise chat are important to b2b softwareHow AI is changing stakeholder relationshipsHow not to overpromise AI capabilities How does Compass relate to BI?How does Compass relate to Dagster and Data Infrastructure?What are the most interesting, innovative, or unexpected ways that you have seen Compass used?What are the most interesting, unexpected, or challenging lessons that you have learned while working on Compass?When is Compass the wrong choice?What do you have planned for the future of Compass?Contact Info LinkedInParting Question From your perspective, what is the biggest gap in the tooling or technology for data management today?Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being used. The AI Engineering Podcast is your guide to the fast-moving world of building AI systems.Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.If you've learned something or tried out a project from the show then tell us about it! Email [email protected] with your story.Links DagsterDagster LabsDagster PlusDagster CompassChris Bergh DataOps EpisodeRise of Medium Code blog postContext EngineeringData StewardInformation ArchitectureConway's LawTemporal durable execution frameworkThe intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Radical Self-Service: Synthesia’s decision-making transformation with Omni and Snowflake When Ed Mancey joined Synthesia as the first data hire, the company had no centralized data stack, conflicting KPIs, and zero self-service. Within a few months, he rolled out Omni on top of Snowflake — enabling business teams to answer their own questions and make better decisions. Now, the sales development team is improving outbound efficiency, sales managers are increasing pipeline conversion, and board reporting runs entirely in Omni. In this session, Edward Mancey will share how they scaled analytics across the business by creating clear lines of responsibility and empowering their business users to move fast and build what they need.

Are dashboards dead? For complex enterprise use cases, the answer might be yes. In this episode, I'm joined by Irina Malkova (VP Data & AI at Salesforce), to discuss her team's transformational journey from building complex dashboards to deploying AI-powered conversational agents. We dive deep into how this shift is not just a change in tooling, but a fundamental change in how users access insights and how data teams measure their impact.

Join us as we cover: The Shift from Dashboards to Agents: We discuss why dashboards can create a high cognitive load and fail users in complex scenarios , and how conversational agents in the flow of work (like Slack) provide targeted, actionable insights and boost adoption.What is Product Telemetry?: Irina explains how telemetry is evolving from a simple engineering observability use case to a critical data source for AI, machine learning, and recommendation systems.Why Standard RAG Fails in the Enterprise: Irina shares why typical RAG approaches break down on dense, entity-rich corporate data (like Salesforce's help docs) where semantic similarity isn't enough, leading to the rise of Graph RAG.The New, Measurable ROI of Data: How moving from BI to agents allows data teams to precisely measure impact, track downstream actions, and finally have a concrete answer to the ROI question that was previously impossible to justify.Data Teams as Enterprise Leaders: Why data teams are uniquely positioned to lead AI transformation, as they hold the enterprise "ontology" and have experience building products under uncertainty.

Snowflake Intelligence au coeur de ces nouveaux usages.

Share your machine learning models, create chatbots, as well as build and deploy insightful dashboards speedily using Taipy with this hands-on book featuring real-world application examples from multiple industries Free with your book: DRM-free PDF version + access to Packt's next-gen Reader Key Features Create visually compelling, interactive data applications with Taipy Bring predictive models to end users and create data pipelines to compare scenarios with what-if analyses Go beyond prototypes to build and deploy production-ready applications using the cloud provider of your choice Purchase of the print or Kindle book includes a free PDF eBook in full color Book Description While data analysts, data scientists, and BI experts have the tools to analyze data, build models, and create compelling visuals, they often struggle to translate these insights into practical, user-friendly applications that help end users answer real-world questions, such as identifying revenue trends, predicting inventory needs, or detecting fraud, without wading through complex code. This book is a comprehensive guide to overcoming this challenge. This book teaches you how to use Taipy, a powerful open-source Python library, to build intuitive, production-ready data apps quickly and efficiently. Instead of creating prototypes that nobody uses, you'll learn how to build faster applications that process large amounts of data for multiple users and deliver measurable business impact. Taipy does the heavy lifting to enable your users to visualize their KPIs, interact with charts and maps, and compare scenarios for better decision-making. You’ll learn to use Taipy to build apps that make your data accessible and actionable in production environments like the cloud or Docker. By the end of this book, you won’t just understand Taipy, you'll be able to transform your data skills into impactful solutions that address real-world needs and deliver valuable insights. Email sign-up and proof of purchase required What you will learn Explore Taipy, its use cases, and how it's different from other projects Discover how to create visually appealing interactive apps, display KPIs, charts, and maps Understand how to compare scenarios to make better decisions Connect Taipy applications to several data sources and services Develop apps for diverse use cases, including chatbots, dashboards, ML apps, and maps Deploy Taipy applications on different types of servers and services Master advanced concepts for simplifying and accelerating your development workflow Who this book is for If you’re a data analyst, data scientist, or BI analyst looking to build production-ready data apps entirely in Python, this book is for you. If your scripts and models sit idle because non-technical stakeholders can’t use them, this book shows you how to turn them into full applications fast with Taipy, so your work delivers real business value. It’s also valuable for developers and engineers who want to streamline their data workflows and build UIs in pure Python.

Découvrez une méthode unique et sans précédent pour décider juste, à chaque instant. 

Imaginez une IA experte, maîtrisant à la fois toute la chaîne Data et la réalité de vos métiers, qui détecte l’invisible dans des milliards de lignes de données, en un instant. 

Sans ouverture de flux, elle vous restitue, en temps réel, une vision claire de la situation et vous propose les meilleures actions, parfaitement alignées avec votre contexte.

Après avoir libéré ses équipes grâce à la Self-BI, le Crédit Agricole d’Île-de-France franchit une nouvelle étape et s’installe à la pointe de l’innovation.

Découvrez la démonstration d’une IA embarquée On-Prem, au cœur d’une plateforme Data unifiée et souveraine, qui réinvente le concept même du Pilotage.