Our latest YAKSS session took a deep dive into Databricks, the unified data, analytics and AI platform transforming how teams manage and scale data solutions. Our BI/ML engineer, Petar Malinovski, delivered a practical and insightful Databricks demo, showing how this powerful platform supports real world data engineering and machine learning workflows.
A Unified Approach to Data & AI
The talk began with an overview of Databricks’ core components: SQL Warehouses for large-scale analytical queries, collaborative notebooks for data science and engineering and the machine learning workspace powered by MLFlow, AutoML and scalable training frameworks. This unified approach highlights why Databricks is increasingly becoming a go-to solution for teams working across the full data lifecycle.
From orchestration with Databricks Workflows to infrastructure management with job and all-purpose clusters, we saw how the platform streamlines daily operations and reduces dependency on multiple external tools.
Data Governance with Unity Catalog
A central theme of the session was Unity Catalog, Databricks’ governance layer that organizes and secures data across clouds. Through clear examples, we learned how metastores, catalogs, schemas, tables and volumes create a structured and governed lakehouse environment making data easier to manage, discover and protect.
Real Use Cases and Hands-On Experience
To bring everything together, Petar shared practical scenarios from real projects, including:
- migrating SSIS solutions into Databricks;
- building Medallion (bronze-silver-gold) architectures;
- improving ETL performance;
- developing and serving ML models with PyTorch and MLFlow;
- implementing DataOps and MLOps best practices.
This mix of theory and hands-on insights helped the team understand not just what Databricks can do, but when and how to use it effectively.
Key Takeaways
The final message was clear: Databricks offers a powerful, all-in-one environment for data and AI, with the flexibility of open-source technologies and the reliability of managed cloud infrastructure. But as with any platform, success depends on thoughtful architecture, cost awareness and strong governance.
We’re grateful to Petar for an excellent session that turned a complex ecosystem into an accessible and engaging learning experience. Another insightful YAKSS session is in the books and we’re already looking forward to the next one.
