Databricks Foundational Workshops

Databricks SQL in Action: Intelligent Data Warehousing, Analytics and BI Workshop

New date coming soon

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

In this workshop, you’ll learn: 

• - How the Data + AI 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.

Unity Catalog: Unified, Open Governance for Data & AI

New date coming soon

Effective governance is essential to democratising 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 + AI Platform features Unity Catalog, a unified and open governance solution for data and AI. Unity Catalog enables organisations 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
• - Utilise 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

Building Modern Applications on Databricks with Lakebase

New date coming soon

Most application stacks are fragmented. Transactions live in one system, analytics in another, and pipelines try to stitch everything together.
That architecture slows development. Teams often spend more time debugging data movement than building features.

This workshop introduces a different approach. You will work with Lakebase, a fully managed Postgres database on Databricks that sits alongside the lakehouse, allowing your applications, analytics, and AI to operate on the same data.

The session demonstrates how modern application teams can move faster when apps, analytics, and AI run on the same data. You will work with Lakebase to spin up a database, connect with Python, run queries, and power real application workflows, showing how the lakehouse can support production-ready applications.

 
In this session, you will learn how to:

• - Run your application and analytics on the same data
• - Set up Lakebase on Databricks and start using it quickly
• - Connect your application using SQL, Python, and standard tools
• - Build features on live data instead of batch copies
• - Push lakehouse data directly into your application
• - Apply governance across both data and applications
• - Get closer to something you could run in production