Congratulations!

Transform and Analyze Data with Microsoft Fabric

Luis Silva

Solution Architect - Data & AI

Data Engineering in Fabric

Diagram showing the components of an end-to-end data analytics solution, including data sources, ingestion, prepare and transform, store, query and visualize and analyze

Data Engineering in Fabric

Diagram showing the components of an end-to-end data analytics solution in Fabric, highlighting Data Pipelines, Spark Notebooks and Dataflows items

Data Factory pipelines: data ingestion
Data Factory dataflows: low-code data transformation and exploration
Notebooks: code-based data transformation and exploration

Data Engineering in Fabric

Diagram showing the components of an end-to-end data analytics solution in Fabric, highlighting Lakehouse and Warehouse items

Lakehouses for storage of files and tables
Warehouses for storage of SQL tables

Implement Star Schema

Designing and implementing Fact and Dimension tables

Implement Star Schema

Normalization and Denormalization
Star Schema vs Snowflake Schema
Slowly Changing Dimensions (SCD)
Special dimension scenarios, including date/time dimensions and multivalued dimensions

Transform, Explore and Analyze Data

Icons representing three tools: SQL, Spark and Dataflows

Data cleansing and filtering
Converting data types
Data aggregation
Merging data

Transform, Explore and Analyze Data

Profiling data
Querying data using the SQL endpoint or the XMLA endpoint

Optimize Performance

Monitoring performance
Implement performance improvements in Fabric items including SQL code, notebooks and dataflows
Scaling up and scaling out Fabric infrastructure
Optimizing Delta lake tables

What's Next?

Badge for the Microsoft Certification Fabric Analytics Engineer Associate

Congratulations!

Transform and Analyze Data with Microsoft Fabric