Insights
Practical writing on custom training, AI implementation, and what's actually working for enterprise teams.
What Is Databricks?
Databricks is a cloud-based data intelligence platform that unifies data engineering, analytics, and AI. Here's what that means for your team.
Ijan Kruizinga
Databricks Academy vs Custom Training
Databricks Academy and custom training serve different goals. Here's how to choose the right approach for your team's situation and learning objectives.
Ijan Kruizinga
Agent Bricks: Build and Govern AI Agents
Agent Bricks is Databricks' framework for building, deploying and governing AI agents on the lakehouse. Here's what data and engineering leads need to know.
Ijan Kruizinga
Databricks Unity Catalog Explained
Unity Catalog is Databricks' unified governance layer for data and AI. Learn how it works, what permissions look like, and who needs it.
Ijan Kruizinga
Databricks vs Power BI: Partners or Rivals?
Databricks and Power BI serve different layers of the data stack. Here's how they fit together, where they overlap, and how to decide what your team needs.
Ijan Kruizinga
The Databricks Lakehouse Explained
The Databricks Lakehouse combines a data lake and data warehouse into one platform. Here's what that means, why it matters, and when it makes sense.
Ijan Kruizinga
Databricks Training for Enterprise Teams
A complete guide to Databricks training for Australian enterprise teams: course options, partner credentials, skill paths, and how to choose the right format.
Ijan Kruizinga
Gemini Data Security for Enterprise
Understand how Google Gemini handles enterprise data, what controls exist, and what your security team needs to configure before rollout.
Ijan Kruizinga
Databricks vs Snowflake: Enterprise Guide
Databricks vs Snowflake: a candid comparison for Australian data and IT leads. Learn which platform fits your workloads, team, and long-term data strategy.
Ijan Kruizinga