What you'll learn

Performance-tuning a deployed Fabric implementation needs proper monitoring for patterns and conditions to assist in an optimal data system. Debugging errors and identifying non-optimized structures can lead to a healthier lakehouse system.

In this course, Microsoft Fabric Data Engineer (DP-700): Monitor and Optimize an Analytics Solution, you’ll gain the ability to use performance monitoring tools to diagnose errors and resolve issues improving the overall performance.

First, you’ll explore monitoring tools for data ingestions, curating various data sources for a gold semantic layer and using alerts to proactively find issues.

Next, you’ll discover errors in pipelines and data flows while debugging the code.

Then, you'll examine tips for common errors in streaming and warehouse data that are using KQL or T-SQL.

Finally, you’ll learn how to optimize performance in a lakehouse for delta tables, use the spark engine in notebooks, and improve eventstreams and eventhouses for near-real-time data.

When you’re finished with this course, you’ll have the skills and knowledge of Microsoft Fabric data engineering needed to pass the DP-700 exam section for monitoring, fixing errors and optimization.