Most organizations run complex cloud data architectures that silo applications, users and data. Join this interactive hands-on workshop to learn how Databricks SQL allows you to operate a multi-cloud lakehouse architecture that delivers data warehouse performance at data lake economics — with up to 12x better price/performance than traditional cloud data warehouses. Here’s what we’ll cover: How Databricks SQL fits in the Data Intelligence Platform, enabling you to operate a multicloud lakehouse architecture that delivers data warehouse performance at data lake economics How to manage and monitor compute resources, data access and users across your lakehouse infrastructure How to query directly on your data lake using your tools of choice or the built-in SQL editor and visualizations How to use AI to increase productivity when querying, completing code or building dashboards Ask your questions during this hands-on lab, and the Databricks experts will guide you.

Most organizations run complex cloud data architectures that silo applications, users and data. Join this interactive hands-on workshop to learn how Databricks SQL allows you to operate a multi-cloud lakehouse architecture that delivers data warehouse performance at data lake economics — with up to 12x better price/performance than traditional cloud data warehouses.Here’s what we’ll cover: How Databricks SQL fits in the Data Intelligence Platform, enabling you to operate a multicloud lakehouse architecture that delivers data warehouse performance at data lake economics How to manage and monitor compute resources, data access and users across your lakehouse infrastructure How to query directly on your data lake using your tools of choice or the built-in SQL editor and visualizations How to use AI to increase productivity when querying, completing code or building dashboards Ask your questions during this hands-on lab, and the Databricks experts will guide you.

Reynold Xin, Co-founder and Chief Architect at Databricks, presented during Data + AI Summit 2024 on Databricks SQL and its advancements and how to drive performance improvements with the Databricks Data Intelligence Platform.

Speakers: Reynold Xin, Co-founder and Chief Architect, Databricks Pearl Ubaru, Technical Product Engineer, Databricks

Main Points and Key Takeaways (AI-generated summary)

Introduction of Databricks SQL: - Databricks SQL was announced four years ago and has become the fastest-growing product in Databricks history. - Over 7,000 customers, including Shell, AT&T, and Adobe, use Databricks SQL for data warehousing.

Evolution from Data Warehouses to Lakehouses: - Traditional data architectures involved separate data warehouses (for business intelligence) and data lakes (for machine learning and AI). - The lakehouse concept combines the best aspects of data warehouses and data lakes into a single package, addressing issues of governance, storage formats, and data silos.

Technological Foundations: - To support the lakehouse, Databricks developed Delta Lake (storage layer) and Unity Catalog (governance layer). - Over time, lakehouses have been recognized as the future of data architecture.

Core Data Warehousing Capabilities: - Databricks SQL has evolved to support essential data warehousing functionalities like full SQL support, materialized views, and role-based access control. - Integration with major BI tools like Tableau, Power BI, and Looker is available out-of-the-box, reducing migration costs.

Price Performance: - Databricks SQL offers significant improvements in price performance, which is crucial given the high costs associated with data warehouses. - Databricks SQL scales more efficiently compared to traditional data warehouses, which struggle with larger data sets.

Incorporation of AI Systems: - Databricks has integrated AI systems at every layer of their engine, improving performance significantly. - AI systems automate data clustering, query optimization, and predictive indexing, enhancing efficiency and speed.

Benchmarks and Performance Improvements: - Databricks SQL has seen dramatic improvements, with some benchmarks showing a 60% increase in speed compared to 2022. - Real-world benchmarks indicate that Databricks SQL can handle high concurrency loads with consistent low latency.

User Experience Enhancements: - Significant efforts have been made to improve the user experience, making Databricks SQL more accessible to analysts and business users, not just data scientists and engineers. - New features include visual data lineage, simplified error messages, and AI-driven recommendations for error fixes.

AI and SQL Integration: - Databricks SQL now supports AI functions and vector searches, allowing users to perform advanced analysis and query optimizations with ease. - The platform enables seamless integration with AI models, which can be published and accessed through the Unity Catalog.

Conclusion: - Databricks SQL has transformed into a comprehensive data warehousing solution that is powerful, cost-effective, and user-friendly. - The lakehouse approach is presented as a superior alternative to traditional data warehouses, offering better performance and lower costs.

Are you looking for an introduction to the Lakehouse and what the related technology is all about? This session is for you. This session explains the value that lakehouses bring to the table using examples of companies that are actually modernizing their data, showing demos throughout. The data lakehouse is the future for modern data teams that want to simplify data workloads, ease collaboration, and maintain the flexibility and openness to stay agile as a company scales.

Come to this session and learn about the full stack, including data engineering, data warehousing in a lakehouse, data streaming, governance, and data science and AI. Learn how you can create modern data solutions of your own.

Talk by: Ari Kaplan and Pearl Ubaru

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Day 1 wrap-up of all the exciting happenings at the Data & AI Summit by Databricks, and hear directly from a variety of attendees on their thoughts of the day. Hosted by Ari Kaplan (Head of Evangelism, Databricks) and Pearl Ubaru (Sr Technical Marketing Engineer, Databricks)

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

With 75k attendees (and 12k in person at the sold-out show), the conference is kicked off by Ari Kaplan (Head of Evangelism, Databricks) and Pearl Ubaru (Sr Technical Marketing Engineer, Databricks). Hear what to expect on the state of data and AI, Databricks, the community, and why the theme is "Generation AI". WE are the generation to make AI a reality, and we all can have a part in shaping this new phase of technology and humanity.