Virtual Event Series
Databricks Specialist Sessions
Dive Deeper into Databricks
As an experienced Databricks user, we’d like to invite you to take a deep dive into a range of topics to help maximise the value and performance of the Databricks platform.
Each Databricks Specialist Session will take an in-depth look at the key challenges you may encounter day-to-day, and how to solve them. Each month, we will cover a different technical subject in depth, including best practices for governance, geospatial data processing, data warehousing and streaming, as well as a detailed look at the platform architecture.
Upcoming Sessions
- Using Databricks with Geospatial Data | 25 February
- Best Practices of Power BI Composite Models on Databricks SQL | 11 March
- From Prototype to Production with MLflow for GenAI | 15 April
Coming Up Next
Using Databricks with Geospatial Data
Duration: 2 hours
This session explores how spatial data unlocks new insights for organisations handling geospatial information at scale. You’ll gain an understanding of Geographic Information Systems (GIS) fundamentals and learn how the physical world is represented in data form.
Whether you’re developing geospatial features, optimising location-based insights, or modernising legacy GIS workloads, this session will equip you with practical knowledge and architectural guidance to make the most of spatial data on the Databricks platform.
Key takeaways:
- - Understand core GIS concepts and how spatial data is modelled on Databricks.
- - Recognise the unique performance and complexity challenges of spatial vs. tabular data.
- - Learn scalable patterns for spatial joins, overlays, and aggregations on large datasets.
- - See reference architectures for modernising legacy GIS and location-analytics workloads
25 February 2026
10:00 AM GMT | 11:00 AM CET
Best Practices of Power BI Composite Models on Databricks SQL
Duration: 1 hour 30 mins
This session shares key lessons for successfully optimising Power BI solutions using composite models in Databricks SQL. You will learn how to design efficient semantic models that balance performance, scalability, and data freshness for business-critical dashboards.
We’ll cover the three essentials of an efficient semantic model: choosing the right Power BI storage modes, designing effective data models, and implementing user-defined aggregations.
Key takeaways:
- - Understand when and how to use DirectQuery, Import, and Dual storage modes with Databricks
- - Design semantic models that deliver both high performance and near real-time analytics
- - Use user-defined aggregations to significantly improve dashboard responsiveness
- - Apply proven patterns and avoid common pitfalls when deploying composite models in production
11 March 2026
10:00 AM GMT | 11:00 AM CET
From Prototype to Production with MLflow for GenAI
Duration: 2 hours
This session introduces MLflow as the open platform for building, evaluating, and deploying production-ready GenAI agents at speed, with core capabilities such as tracing, evaluation, versioning, and the AI Gateway, which provides deep visibility into agent behaviour while simplifying debugging and improving reliability at scale.
We’ll also cover MLflow’s newest features brought to life through a live demo showcasing end-to-end tracing, evaluation, and monitoring in action. Whether you’re just starting with GenAI or scaling existing agents, you’ll leave with a clear phased adoption strategy—from initial tracing through full production monitoring—to deliver high-quality, cost-efficient, and accountable GenAI applications.
Key takeaways:
- - Use MLflow to support the full GenAI agent lifecycle, from experimentation to production monitoring.
- - Apply tracing, evaluation, and LLM judges to understand and improve complex agent behaviour
- - Leverage the newest MLflow features, including prompt optimisation and the Prompt Registry API for governed, reusable prompt management
- - Follow a phased adoption strategy for robust monitoring, evaluation, and governance of GenAI systems on Databricks
Ideal for: ML engineers, data scientists, and platform teams building or operating GenAI systems on Databricks
15 April 2026
10:00 AM BST | 11:00 AM CEST
