microsoft fabrics and databricks

It depends on your career goals, but in general learning Microsoft Fabric first is a great foundation.

• Databricks is not included in Microsoft Fabric. Fabric has its own Spark-based experience (Fabric Data Engineering and Data Science) that lets you work with notebooks, Spark jobs, Delta tables, and lakehouses without requiring Databricks.

• If you're working mainly in the Microsoft ecosystem (Power BI, Fabric, Azure), Fabric is often sufficient for many analytics, BI, and data engineering workloads.

• Databricks is still worth learning if you expect to work in organizations that use multi-cloud environments (AWS, Azure, GCP), large-scale data engineering, advanced ML, or already have an established Databricks platform.

So the learning path I'd recommend is:

1. Master Microsoft Fabric.

2. Learn Spark fundamentals (these transfer to Databricks).

3. If your role or employer requires it, pick up Databricks afterward—it will be much easier because many concepts (Spark, Delta Lake, notebooks, SQL) are shared.

In short: Fabric is enough to get started and build a strong career in the Microsoft data ecosystem, but learning Databricks later will broaden your opportunities rather than replace Fabric.