In PacificSource Health Plans, a health insurance company in the US, we are on a successful multi-year journey to migrate all of our data and analytics ecosystem to Databricks Enterprise Data Warehouse (lakehouse). A particular obstacle on this journey was a reporting data mart which relied on copious amounts of legacy SAS code that applied sophisticated business logic transformations for membership, claims, premiums and reserves. This core data mart was driving many of our critical reports and analytics. In this session we will share the unique and somewhat unexpected challenges and complexities we encountered in migrating this legacy SAS code. How our partner (T1A) leveraged automation technology (Alchemist) and some unique approaches to reverse engineer (analyze), instrument, translate, migrate, validate and reconcile these jobs; and what lessons we learned and carried from this migration effort.

Unlock the full potential of your BI tools with Databricks. This session explores how features like Photon, Databricks SQL, Liquid Clustering, AI/BI Genie and Publish to Power BI enhance performance, scalability and user experience. Learn how Databricks accelerates query performance, optimizes data layouts and integrates seamlessly with BI tools. Gain actionable insights and best practices to improve analytics efficiency, reduce latency and drive better decision-making. Whether migrating from a data warehouse or optimizing an existing setup, this talk provides the strategies to elevate your BI capabilities.

This session is repeated. If you are brand new to Databricks SQL and want to get a lightning tour of this intelligent data warehouse, this session is for you. Learn about the architecture of Databricks SQL. Then show how simple, streamlined interfaces are making it easier for analysts, developers, admins and business users to get their jobs done and questions answered. We’ll show how easy it is to create a warehouse, get data, transform it and build queries and dashboards. By the end of the session, you’ll be able to build a Databricks SQL warehouse in 5 minutes.

This course is designed for data professionals who want to explore the data warehousing capabilities of Databricks. Assuming no prior knowledge of Databricks, it provides an introduction to leveraging Databricks as a modern cloud-based data warehousing solution. Learners will explore how use the Databricks Data Intelligence Platform to ingest, transform, govern, and analyze data efficiently. Learners will also explore Genie, an innovative Databricks feature that simplifies data exploration through natural language queries. By the end of this course, participants will be equipped with the foundational skills to implement and optimize a data warehouse using Databricks. Pre-requisites: Basic understanding of SQL and data querying concepts General knowledge of data warehousing concepts, including tables, schemas, and ETL/ELT processes is recommended Some experience with BI and/or data visualization tools is helpful but not required Labs: Yes

This course offers a deep dive into designing data models within the Databricks Lakehouse environment, and understanding the data products lifecycle. Participants will learn to align business requirements with data organization and model design leveraging Delta Lake and Unity Catalog for defining data architectures, and techniques for data integration and sharing. Prerequisites: Foundational knowledge equivalent to Databricks Certified Data Engineer Associate and familiarity with many topics covered in Databricks Certified Data Engineer Professional. Experience with: Basic SQL queries and table creation on Databricks Lakehouse architecture fundamentals (medallion layers) Unity Catalog concepts (high-level) [Optional] Familiarity with data warehousing concepts (dimensional modeling, 3NF, etc.) is beneficial but not mandatory. Labs: Yes

In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data engineering workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with objects in Databricks such as catalogs, schemas, volumes, tables, compute clusters and notebooks. You will then follow a basic data engineering workflow to perform tasks such as creating and working with tables, ingesting data into Delta Lake, transforming data through the medallion architecture, and using Databricks Workflows to orchestrate data engineering tasks. You’ll also learn how Databricks supports data warehousing needs through the use of Databricks SQL, DLT, and Unity Catalog.

This course provides a comprehensive overview of Databricks’ modern approach to data warehousing, highlighting how a data lakehouse architecture combines the strengths of traditional data warehouses with the flexibility and scalability of the cloud. You’ll learn about the AI-driven features that enhance data transformation and analysis on the Databricks Data Intelligence Platform. Designed for data warehousing practitioners, this course provides you with the foundational information needed to begin building and managing high-performant, AI-powered data warehouses on Databricks. This course is designed for those starting out in data warehousing and those who would like to execute data warehousing workloads on Databricks. Participants may also include data warehousing practitioners who are familiar with traditional data warehousing techniques and concepts and are looking to expand their understanding of how data warehousing workloads are executed on Databricks.