Business Impact Accelerator: Answering Business Questions with Genie

This get started course introduces Databricks Lakebase, a fully managed PostgreSQL service built into the Databricks Data Intelligence Platform that brings operational (OLTP) and analytical (OLAP) workloads closer together.

The course begins with a conceptual lecture that compares OLTP and OLAP systems, explaining their different performance characteristics, storage models, and typical use cases. You will also explore the challenges organizations face when maintaining separate transactional databases and analytical platforms, including data movement, latency, and architectural complexity.

You will then learn how Databricks Lakebase helps address these challenges by providing a PostgreSQL-compatible operational database that integrates directly with the Databricks Lakehouse, enabling operational applications and analytics to work together within a unified platform.

This is a Get Started course, so the focus is on understanding the core concepts and basic workflows for working with Lakebase. Building full production applications on top of Lakebase is outside the scope of this course.

By the end of the course, you will understand how Lakebase enables organizations to bridge operational systems and analytics within a single governed platform powered by Unity Catalog and the Databricks Lakehouse.

You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.

Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.

This course is a comprehensive, hands-on introduction to the Databricks Data Intelligence Platform. You will follow a single end-to-end journey that starts in the workspace and finishes with an introduction to AI and machine learning, covering the everyday skills you need to work with data on Databricks.

The course covers:

• Navigating the Databricks workspace, compute options, and the Lakehouse versus Genie experiences.

• Understanding and ingesting data with Unity Catalog, including file upload and the Catalog Explorer.

• Working in Databricks notebooks and using Genie Code to write and debug code.

• Querying data with SQL, managing saved queries, and building dashboards and visualizations.

• Exploring data in natural language with Genie Agents.

• An introduction to AI and machine learning with MLflow and the Data Science Agent.

By the end of the course, you will be comfortable navigating Databricks, finding and governing data in Unity Catalog, writing SQL and notebook code with AI assistance, building dashboards, and exploring data with Genie.

Languages Available: English | 日本語 | 한국어

Master scalable data processing with Apache Spark in this course. Learn to build efficient ETL pipelines, perform advanced analytics, and optimize distributed data transformations using Spark’s DataFrame API. Explore grouping, aggregation, joins, set operations, and window functions. Work with complex data types like arrays, maps, and structs while applying best practices for performance optimization.

Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.

Languages Available: English | 日本語 | 한국어