Duration
1 day
Overview
Relational data warehouses are at the center of most enterprise business intelligence (BI) solutions. While the specific details may vary across data warehouse implementations, a common pattern based on a denormalized, multidimensional schema has emerged as the standard design for a relational data warehouse.
Microsoft Fabric's data warehouse is a modern version of the traditional data warehouse. It centralizes and organizes data from different departments, systems, and databases into a single, unified view for analysis and reporting purposes. Fabric's data warehouse provides full SQL semantics, including the ability to insert, update, and delete data in the tables. Fabric's data warehouse is unique because it's built on the Lakehouse, which is stored in Delta format and can be queried using SQL. It's designed for use by the whole data team, not just data engineers.
Fabric's data warehouse experience is designed to address these challenges. Fabric enables data engineers, analysts, and data scientists to work together to create and query a data warehouse that is optimized for their specific needs.
In this module, you'll learn about data warehouses in Fabric, create a data warehouse, load, query, and visualize data.
Outline
- Understand data warehouse fundamentals
- Understand Fabric's data warehouse experience
- Design a data warehouse
- Tables in a data warehouse
- Special types of dimension tables
- Data warehouse schema designs
- Understand data warehouses in Fabric
- Describe a data warehouse in Fabric
- Ingest data into your data warehouse
- Create tables
- Table considerations
- Query and transform data
- Query data using the SQL query editor
- Query data using the Visual query editor
- Prepare data for analysis and reporting
- Build relationships
- Create measures
- Hide fields
- Understand semantic models
- Understand the default semantic model
- Visualize data
- Secure and monitor your data warehouse
- Security
- Workspace permissions
- Item permissions
- Monitoring
- Query monitoring
- Exercise - Analyze data in a data warehouse
Summary
In this module, you learned about data warehouses and dimensional modeling, created a data warehouse, loaded, queried, and visualized data, and described semantic models and how they're used for downstream reporting.
Programme scope, delivery arrangements and suitability are confirmed during enquiry.