Databricks Foundational Workshops

Learn how to build, enhance, and deploy AI systems by combining traditional machine learning with Generative AI on the Databricks Platform. This hands-on workshop shows how governed data, modern ML workflows, and GenAI capabilities come together to power secure, scalable AI innovation.

In this session, you will get the chance to:

• Learn how to utilize vector search within Databricks to enhance your Generative AI applications, making it easier to find and retrieve information based on similarity.

• Get hands-on experience with embedding models to understand how data can be transformed into a format that generative models can use more effectively for tasks like recommendation systems or content generation.

• Dive into the AI Playground on Databricks to experiment with foundational models, explore various AI functions, and see how they can be applied in real-world scenarios.

• Understand how to pull open-source foundational models into your workflows, integrating them into experiments and pipelines for generating text, images, and more.

• Govern all your AI assets using Unity Catalog

This introductory, hands-on workshop is built for data engineers and data architects who want practical experience with modern data engineering on Databricks.

You’ll work directly in your own lab environment and learn how to design, build, and operate reliable data pipelines using real-world use cases. You’ll leave with hands-on experience using GitHub, ingesting data from multiple sources, and operationalizing pipelines end to end.

In this session, you will learn:

• Introduction to Lakeflow and the Data Intelligence Platform

• Getting started with Declarative Pipelines, Streaming Tables, and Materialized Views

• Working with a realistic data streaming use case

• Mastering Lakeflow Jobs with advanced control flow and triggers

• Generative AI for Data Engineers: Genie and Databricks Assistant

• Understanding data governance and lineage with Unity Catalog

• Benefits of Serverless Compute

Effective governance is essential to democratizing data and AI in the age of LLMs and generative AI. Enterprises struggle with fragmented governance across databases, warehouses, lakes, and diverse data formats, which complicates discovery, access permissions, data usage, audits, and sharing. Additionally, users often cannot access the right data from their preferred tools, leading to vendor lock-in. Managing ML models and AI tools for regulatory compliance adds another layer of complexity.

Databricks Data Intelligence Platform features Unity Catalog, a unified and open governance solution for data and AI. Unity Catalog enables organizations to seamlessly govern structured and unstructured data, machine learning models, notebooks, dashboards, and files across any cloud or platform. With wide interoperability across the Delta and Iceberg ecosystems, users can access data effortlessly from any tool of their choice, ensuring flexibility and eliminating vendor lock-in.

In this session, you will learn how to:

• Create a unified catalog for structured/unstructured data, ML models, and features, AI tools
• Utilize context-aware natural language search and discovery
• Implement access permissions and audit data access
• Access data and AI assets from any tool open APIs
• Use AI to monitor data and ML pipeline quality
• Share data effortlessly across clouds, regions, or platforms with open source Delta Sharing

Most organizations run complex cloud data architectures that silo applications, users and data. As a result, most analysis is performed on stale data and there’s no single source of truth of data for analytics - making it difficult to scale trusted insights across teams.

Join this interactive hands-on workshop to learn how Databricks SQL enables a multicloud lakehouse architecture that delivers data warehouse performance at data lake economics — with up to 12x better price/performance than traditional cloud data warehouses. You’ll discover how data architects can unify infrastructure and governance, while data analysts and BI teams can work with the freshest, most complete data—and accelerate insights using Databricks’ native AI/BI capabilities along with their favorite BI tools.

Whether you’re building a scalable foundation or delivering insights to the business, this workshop is designed to help you modernize your analytics stack and make AI-powered BI a reality.

In this workshop, you’ll learn:

• How the Data Intelligence Platform and Databricks SQL support a unified, multicloud lakehouse architecture
• How to manage and monitor compute, data access, and users across your lakehouse using Databricks SQL
• How data teams and analysts can query directly on your data lake using the built-in SQL editor, AI/BI or their preferred BI tools.
• How to use AI-assisted features like AI-assisted code completion, automated dashboard creation and natural language querying via AI/BI Genie,to increase productivity and scale self-service analytics.