Congratulations!

1. Congratulations!

Congratulations on completing this course on transforming and analyzing data with Microsoft Fabric! Let's quickly recap what you've learned.

2. Data Engineering in Fabric

We talked about an end-to-end data analytics solution that ingests data from multiple sources, transforms the data and stores it ready for users to interact with.

3. Data Engineering in Fabric

We had a look at the different items that you can create in Fabric to support data engineering tasks: Data Factory pipelines for data ingestion, Data Factory dataflows for low-code data transformation and exploration, and Notebooks for code-based data transformation and exploration

4. Data Engineering in Fabric

For storing the data, we learned about Fabric lakehouses for files and tables, and warehouses for SQL tables.

5. Implement Star Schema

We learned about the measures and attributes that describe business events like a product sale, and designing and implementing dimension and fact tables that make up the star schema that models the business event.

6. Implement Star Schema

We learned about the data normalization and denormalization, and the differences between star schemas and snowflake schemas. We also covered the challenge of slowly changing dimensions and learned about special dimension scenarios such as datetime dimensions and multivalued dimensions.

7. Transform, Explore and Analyze Data

We learned about key data transformation operations such as cleansing and filtering, converting data types, and aggregating and merging data. We did exercises to practice how to perform these transformations using different tools including SQL scripts, Spark notebooks and Dataflows.

8. Transform, Explore and Analyze Data

We also talked about exploring and profiling data, using tools outside of Fabric to query data using the SQL endpoint and the XMLA endpoint.

9. Optimize Performance

Finally, we talked about tools to monitor Fabric performance and mechanisms to improve performance of individual Fabric items. We also learned about scaling up and scaling out as a way to increase Fabric capacity, and delta lake table optimization operations.

10. What's Next?

This course was designed to cover key topics required to pass Microsoft’s Fabric Analytics Engineer Associate certification, also known as DP-600. In particular, the topics of this course address the "Prepare data" skill, which is about 45% of the exam. It’s important to note that passing the certification exam will likely require deeper exploration into many of these topics. That being said, now that you have taken this course and have some hands-on experience with Fabric, many of the topics in the certification exam should be familiar to you.

11. Congratulations!

You've gained valuable knowledge and skills that are essential to transform and analyze data in Microsoft Fabric and can also prepare you to pass the Fabric Analytics Engineer Associate certification. Thank you for choosing this course, and best of luck in all your future Fabric endeavors!

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