Managing cloud costs requires accurate resource tagging, but maintaining completeness and accuracy is a challenge. In this session, Mitchell Ertle (Senior Partner Solutions Architect) and Josue Bogran (Data & AI Architect) demonstrate how Sigma and Databricks combine to streamline FinOps and resource management with AI-driven cost attribution and workflow automation.

Through a practical demonstration, you'll see:

Identify and classify untagged Databricks pipelines with a cost attribution app Use GenAI from Databricks to suggest tags with human-in-the-loop approval Enable bidirectional data flow between Sigma and Databricks for real-time updates Automate workflows with Sigma’s actions framework Ensure security and governance by inheriting Unity Catalog permissions Discover why this combination is powerful—Sigma provides intuitive application building while Databricks delivers computation, AI/ML capabilities, and data storage. These platforms create solutions business users can interact with directly, without technical expertise.

Whether in data engineering, finance, or operations, learn how Sigma + Databricks can automate workflows, optimize costs, and drive business impact.

➡️ Learn more about Data Apps: https://www.sigmacomputing.com/product/data-applications?utm_source=youtube&utm_medium=organic&utm_campaign=data_apps_conference&utm_content=pp_data_apps

➡️ Sign up for your free trial: https://www.sigmacomputing.com/go/free-trial?utm_source=youtube&utm_medium=video&utm_campaign=free_trial&utm_content=free_trial

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🎙️ Future of Data and AI Podcast: Episode 06 with Robin Sutara What do Apache, Excel, Microsoft, and Databricks have in common? Robin Sutara! From being a technician for Apache helicopters to leading global data strategy at Microsoft and now Databricks, Robin Sutara’s journey is anything but ordinary. In this episode, she shares how enterprises are adopting AI in practical, secure, and responsible ways—without getting lost in the hype. We dive into how Databricks is evolving beyond the Lakehouse to power the next wave of enterprise AI—supporting custom models, Retrieval-Augmented Generation (RAG), and compound AI systems that balance innovation with governance, transparency, and risk management. Robin also breaks down the real challenges to AI adoption—not technical, but cultural. She explains why companies must invest in change management, empower non-technical teams, and embrace diverse perspectives to make AI truly work at scale. Her take on job evolution, bias in AI, and the human side of automation is both refreshing and deeply relevant. A sharp, insightful conversation for anyone building or scaling AI inside the enterprise—especially in regulated industries where trust and explainability matter as much as innovation.

Summary In this episode of the Data Engineering Podcast, host Tobias Macy welcomes back Shinji Kim to discuss the evolving role of semantic layers in the era of AI. As they explore the challenges of managing vast data ecosystems and providing context to data users, they delve into the significance of semantic layers for AI applications. They dive into the nuances of semantic modeling, the impact of AI on data accessibility, and the importance of business logic in semantic models. Shinji shares her insights on how SelectStar is helping teams navigate these complexities, and together they cover the future of semantic modeling as a native construct in data systems. Join them for an in-depth conversation on the evolving landscape of data engineering and its intersection with AI.

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data managementData 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 Shinji Kim about the role of semantic layers in the era of AIInterview IntroductionHow did you get involved in the area of data management?Semantic modeling gained a lot of attention ~4-5 years ago in the context of the "modern data stack". What is your motivation for revisiting that topic today?There are several overlapping concepts – "semantic layer," "metrics layer," "headless BI." How do you define these terms, and what are the key distinctions and overlaps?Do you see these concepts converging, or do they serve distinct long-term purposes?Data warehousing and business intelligence have been around for decades now. What new value does semantic modeling beyond practices like star schemas, OLAP cubes, etc.?What benefits does a semantic model provide when integrating your data platform into AI use cases?How is it different between using AI as an interface to your analytical use cases vs. powering customer facing AI applications with your data?Putting in the effort to create and maintain a set of semantic models is non-zero. What role can LLMs play in helping to propose and construct those models?For teams who have already invested in building this capability, what additional context and metadata is necessary to provide guidance to LLMs when working with their models?What's the most effective way to create a semantic layer without turning it into a massive project? There are several technologies available for building and serving these models. What are the selection criteria that you recommend for teams who are starting down this path?What are the most interesting, innovative, or unexpected ways that you have seen semantic models used?What are the most interesting, unexpected, or challenging lessons that you have learned while working with semantic modeling?When is semantic modeling the wrong choice?What do you predict for the future of semantic modeling?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 SelectStarSun MicrosystemsMarkov Chain Monte CarloSemantic ModelingSemantic LayerMetrics LayerHeadless BICubePodcast EpisodeAtScaleStar SchemaData VaultOLAP CubeRAG == Retrieval Augmented GenerationAI Engineering Podcast EpisodeKNN == K-Nearest NeighbersHNSW == Hierarchical Navigable Small Worlddbt Metrics LayerSoda DataLookMLHexPowerBITableauSemantic View (Snowflake)Databricks GenieSnowflake Cortex AnalystMalloyThe intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

SAP and Databricks recently announced their landmark partnership to simplify customer’s data landscapes. Join us to see how we are coming together to shift how applications and data platforms work together. From curated SAP data products to zero-copy integration, learn how SAP Business Data Cloud with SAP Databricks enables your data architecture of choice to deliver insights your business can trust.

Data intelligence rapidly transforms businesses, enabling them to make more informed decisions, streamline operations, and gain a competitive edge. At Google Cloud Next '25, we are excited to present a thought-provoking session on the power of data intelligence in partnership with Databricks on Google Cloud and Digital Turbine. Our speakers from Databricks and Digital Turbine will share their insights on how organizations can leverage data to drive innovation and growth. Join us for this engaging discussion and gain valuable insights on how data intelligence can help your organization thrive in the digital age.

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

This session brings together leading product experts from Google Cloud, Anthropic, Oracle, Databricks, and SAP to explore the five essential strategies for enterprises to successfully leverage AI and data. Attendees will gain valuable insights from real-world AI implementations, learn from the successes and challenges faced by global customers, and receive practical guidance on how to translate these strategies into actionable plans for their own AI journeys.

The role of data and AI engineers is more critical than ever. With organizations collecting massive amounts of data, the challenge lies in building efficient data infrastructures that can support AI systems and deliver actionable insights. But what does it take to become a successful data or AI engineer? How do you navigate the complex landscape of data tools and technologies? And what are the key skills and strategies needed to excel in this field?  Deepak Goyal is a globally recognized authority in Cloud Data Engineering and AI. As the Founder & CEO of Azurelib Academy, he has built a trusted platform for advanced cloud education, empowering over 100,000 professionals and influencing data strategies across Fortune 500 companies. With over 17 years of leadership experience, Deepak has been at the forefront of designing and implementing scalable, real-world data solutions using cutting-edge technologies like Microsoft Azure, Databricks, and Generative AI. In the episode, Richie and Deepak explore the fundamentals of data engineering, the critical skills needed, the intersection with AI roles, career paths, and essential soft skills. They also discuss the hiring process, interview tips, and the importance of continuous learning in a rapidly evolving field, and much more. Links Mentioned in the Show: AzureLibAzureLib Academy Connect with DeepakGet Certified! Azure FundamentalsRelated Episode: Effective Data Engineering with Liya Aizenberg, Director of Data Engineering at AwaySign up to attend RADAR: Skills Edition  New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Time Series Analysis with Spark provides a practical introduction to leveraging Apache Spark and Databricks for time series analysis. You'll learn to prepare, model, and deploy robust and scalable time series solutions for real-world applications. From data preparation to advanced generative AI techniques, this guide prepares you to excel in big data analytics. What this Book will help me do Understand the core concepts and architectures of Apache Spark for time series analysis. Learn to clean, organize, and prepare time series data for big data environments. Gain expertise in choosing, building, and training various time series models tailored to specific projects. Master techniques to scale your models in production using Spark and Databricks. Explore the integration of advanced technologies such as generative AI to enhance predictions and derive insights. Author(s) Yoni Ramaswami, a Senior Solutions Architect at Databricks, has extensive experience in data engineering and AI solutions. With a focus on creating innovative big data and AI strategies across industries, Yoni authored this book to empower professionals to efficiently handle time series data. Yoni's approachable style ensures that both foundational concepts and advanced techniques are accessible to readers. Who is it for? This book is ideal for data engineers, machine learning engineers, data scientists, and analysts interested in enhancing their expertise in time series analysis using Apache Spark and Databricks. Whether you're new to time series or looking to refine your skills, you'll find both foundational insights and advanced practices explained clearly. A basic understanding of Spark is helpful but not required.

Serhii Sokolenko, founder at Tower Dev and former product manager at tech giants like Google Cloud, Snowflake, and Databricks, joined Yuliia to discuss his journey building a next-generation compute platform. Tower Dev aims to simplify data processing for data engineers who work with Python. Serhii explains how Tower addresses three key market trends: the integration of data engineering with AI through Python, the movement away from complex distributed processing frameworks, and users' desire for flexibility across different data platforms. He explains how Tower makes Python data applications more accessible by eliminating the need to learn complex frameworks while automatically scaling infrastructure. Sergei also shares his perspective on the future of data engineering, noting in which ways AI will transform the profession.Tower Dev - https://tower.dev/Serhii's Linkedin - https://www.linkedin.com/in/ssokolenko/

Use SQL to get the data you need in no time at all! Learn to read and write basic queries, troubleshoot common problems, and control your own business data in just 24 short lessons–no programming experience required! SQL has been designed to be as close to English as possible—anyone can learn it! Learn SQL in a Month of Lunches helps you add this lucrative and highly sought-after skill to your resume in just 24 fun and friendly lessons. The book emphasizes practical uses for the language in the real-world, so you’ll just learn the most useful skills for business data analysis. Inside Learn SQL in a Month of Lunches you’ll discover how to: Set up your first database with MySQL Write your own SQL queries See only the data you need from large datasets Connect different sets of data Analyze data with functions and aggregations Master basic data manipulation techniques Save queries in stored procedures and views Create tables to store data efficiently Read and improve SQL written by others If you use Excel, Tableau, or PowerBI to crunch business data, you’ve probably seen a lot of SQL already. And guess what? It’s easy to master the most useful parts of SQL! In just a few quick lessons, Learn SQL in a Month of Lunches will get you writing your own queries, modifying existing SQL statements, and working with data like a pro. 25-year SQL veteran Jeff Iannucci makes SQL a snap through hands-on lab exercises, relevant code examples, and easy-to-understand language. About the Technology SQL, Structured Query Language, is the standard way to query, create, and manage relational databases like SQL Server, PostgreSQL, and Oracle. It’s also a superpower for data analysts who need to go beyond spreadsheets and BI dashboarding tools. SQL is easy to read and understand, and with this book (and a little practice) you’ll be pulling data, tweaking tables, and cranking out amazing reports and presentations in no time at all! About the Book Learn SQL in a Month of Lunches introduces SQL to data analysts and other aspiring data pros with no prior experience using relational databases. In it, you’ll complete 24 short lessons, each of which teaches an essential SQL skill for retrieving, filtering, and analyzing data. You’ll practice each new technique with a friendly hands-on lab designed to take about 15 minutes, as you learn to write queries that deliver the exact data you need. Along the way, you’ll build a valuable intuition for how databases operate in real business scenarios. What's Inside Get the data you need from any relational database Filter, sort, and group data Combine data from multiple tables Create, update, and delete data About the Reader For students, aspiring data analysts, software developers, and anyone else who wants to work with relational databases. About the Author Jeff Iannucci is a Senior Consultant with Straight Path Solutions. For over 20 years, he has worked extensively with SQL in sectors such as healthcare, finance, retail sales, and government. Quotes An essential guide. Jeff has carefully developed each chapter to ensure clarity and comprehensiveness, making complex concepts accessible and practical. - Buck Woody, Microsoft The fastest and the most effective way to learn SQL, regardless of your background or technical knowledge level. - Kevin Kline, author of SQL in a Nutshell Explains concepts straightforwardly to help the reader grow their skills over a month of sessions. - Steve Jones, SQL Server Central Great selection of bite-sized, digestible courses to complement your lunch arrangement. It leaves you smarter every day. - Simon Tschöke, Databricks

Data engineers proficient in Databricks are currently in high demand. As organizations gather more data than ever before, skilled data engineers on platforms like Databricks become critical to business success. The Databricks Data Engineer Associate certification is proof that you have a complete understanding of the Databricks platform and its capabilities, as well as the essential skills to effectively execute various data engineering tasks on the platform. In this comprehensive study guide, you will build a strong foundation in all topics covered on the certification exam, including the Databricks Lakehouse and its tools and benefits. You'll also learn to develop ETL pipelines in both batch and streaming modes. Moreover, you'll discover how to orchestrate data workflows and design dashboards while maintaining data governance. Finally, you'll dive into the finer points of exactly what's on the exam and learn to prepare for it with mock tests. Author Derar Alhussein teaches you not only the fundamental concepts but also provides hands-on exercises to reinforce your understanding. From setting up your Databricks workspace to deploying production pipelines, each chapter is carefully crafted to equip you with the skills needed to master the Databricks Platform. By the end of this book, you'll know everything you need to ace the Databricks Data Engineer Associate certification exam with flying colors, and start your career as a certified data engineer from Databricks! You'll learn how to: Use the Databricks Platform and Delta Lake effectively Perform advanced ETL tasks using Apache Spark SQL Design multi-hop architecture to process data incrementally Build production pipelines using Delta Live Tables and Databricks Jobs Implement data governance using Databricks SQL and Unity Catalog Derar Alhussein is a senior data engineer with a master's degree in data mining. He has over a decade of hands-on experience in software and data projects, including large-scale projects on Databricks. He currently holds eight certifications from Databricks, showcasing his proficiency in the field. Derar is also an experienced instructor, with a proven track record of success in training thousands of data engineers, helping them to develop their skills and obtain professional certifications.

If you're looking to build production-ready AI applications that can reason and retrieve external data for context-awareness, you'll need to master--;a popular development framework and platform for building, running, and managing agentic applications. LangChain is used by several leading companies, including Zapier, Replit, Databricks, and many more. This guide is an indispensable resource for developers who understand Python or JavaScript but are beginners eager to harness the power of AI. Authors Mayo Oshin and Nuno Campos demystify the use of LangChain through practical insights and in-depth tutorials. Starting with basic concepts, this book shows you step-by-step how to build a production-ready AI agent that uses your data. Harness the power of retrieval-augmented generation (RAG) to enhance the accuracy of LLMs using external up-to-date data Develop and deploy AI applications that interact intelligently and contextually with users Make use of the powerful agent architecture with LangGraph Integrate and manage third-party APIs and tools to extend the functionality of your AI applications Monitor, test, and evaluate your AI applications to improve performance Understand the foundations of LLM app development and how they can be used with LangChain

It’s time for another episode of the Data Engineering Central Podcast. In this episode, we cover … * AWS Lambda + DuckDB and Delta Lake (Polars, Daft, etc). * IAC - Long Live Terraform. * Databricks Data Quality with DQX. * Unity Catalog releases for DuckDB and Polars * Bespoke vs Managed Data Platforms * Delta Lake vs. Iceberg and UinFORM for a single table. Thanks for b…

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit dataengineeringcentral.substack.com/subscribe

Tag Manager Italia collaborated with CNH to design and implement a global GA4-based data strategy, unifying analytics across their extensive operations. This session explores the whole project, with a focus on how advanced tools like BigQuery and Databricks enabled data centralization, while custom Power BI dashboards and privacy-compliant frameworks empowered informed decisions and enhanced marketing and business outcomes.

In todays episode of Data Engineering Central Podcast we talk about a few hot topics, AWS S3 Tables, Databricks raising money, are Data Contracts Dead, and the Lake House Storage Format battle! It's a good one, buckle up!

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit dataengineeringcentral.substack.com/subscribe

🌟 Session Overview 🌟

Session Name: Supernovas, Black Holes, and Streaming Data: A Journey in Space with Apache Kafka data streams from NASA Speaker: Frank Munz Session Description: In this fun, hands-on, and in-depth How-To, we explore NASA's GCN project, which publishes various events in space as Kafka topics.

The focus of my talk is on end-to-end data engineering, from consuming the data and ELT-ing the stream, to using generative AI tools for analytics.

We will analyze GCN data in real time, specifically targeting the data stream from exploding supernovas. This data triggers dozens of terrestrial telescopes to potentially reposition and point toward the event.

The speaker will kick off the session by contrasting various ways of ingesting and transforming the data, discussing their trade-offs: Should you use a declarative data pipeline, or can a data analyst manage with SQL only? Alternatively, when would it be better to follow the classic approach of orchestrating Spark notebooks to get the data ingested?

He will answer the question: Does a data engineer working with streaming data benefit from generative AI-based tools and assistants today? Is it worth it, or is it just hype?

The demo is easy to replicate at home, and Frank will share the notebooks in a GitHub repository so you can analyze real NASA data yourself!

This session is ideal for data engineers, data architects who enjoy some coding, generative AI enthusiasts, or anyone fascinated by technology and the sparkling stars in the night sky.

While the focus is clearly on tech, the demo will run on the open-source and open-standards-based Databricks Intelligence Platform (so inevitably, you'll get a high-level overview here too).

🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

🌟 Session Overview 🌟

Session Name: Leveraging Azure PaaS for Real-time Social Media Analysis by Building Streaming Dashboard Speaker: Raghav Matta Session Description: In this session, Raghav and Sundar will delve into a practical business scenario focusing on real-time social media analysis using Azure PaaS offerings.

1. They will begin by addressing a prevalent business challenge concerning social media sentiment analysis.

2. Next, speakers explore a range of Azure services including Azure Functions, Logic Apps, Cognitive Services, Stream Analytics, PowerBI, and Azure Databricks.

3. Moving forward, they will demonstrate how to gather live data in real-time utilizing Azure Cognitive Services Bing Web Search API. Subsequently, they will analyze the data using Azure Stream Analytics and visualize insights using PowerBI.

This course combines hands-on labs with theoretical curriculum aligned with the 'Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution'.

For further information and resources, please refer to: https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-twitter-sentiment-analysis-trends https://microsoftlearning.github.io/AI-102-AIEngineer/Instructions/05-analyze-text.html 🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

Azure Databricks enhances the lakehouse experience in Azure by seamlessly integrating data and AI solutions for faster value. Catalog data, schema, and tables in Unity Catalog are readily available, supporting data engineering, data science, real-time intelligence, and optimized performance, delivering blazing fast insights with Power BI.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Lindsey Allen * Robert Saxby

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK203 | English (US) | Data

MSIgnite

Azure Databricks is a first-party service on Microsoft Azure, offering seamless native integration with vital Azure Services and workloads that add value. Join us to learn about what is new in Azure Databricks. We'll also share how Azure Databricks unlocks the power of AI, enabling businesses to leverage machine learning for predictive insights, automation, and innovation—ultimately driving smarter decision-making and long-term business growth.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Lindsey Allen * Robert Saxby

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK208 | English (US) | Data

MSIgnite

Customers are embracing unified data and analytics to achieve more with their data and get ready for AI transformation, opening up a large and high growth opportunity for Microsoft partners. Microsoft’s expanding set of AI-powered toolset, including Fabric and Azure Databricks, provide open and extensible platforms for customers to accelerate their AI journey. Understand the narrative, and the resources for positioning yourself to profit from this opportunity.

To learn more, please check out these resources: * https://aka.ms/Ignite24Plan-MicrosoftFabric * https://aka.ms/DataAICiaB * https://aka.ms/FabricPartnerResources * https://aka.ms/dreams * https://aka.ms/JoinFabricPartnerCommunity * https://www.fabricconf.com

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Ashley Asdourian * Wangui McKelvey

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK210 | English (US) | Data

MSIgnite