This repo contains the samples demonstrating the usage of Power BI with Databricks SQL. The objective of these samples is to demonstrate reference implementation and some of the best practices using Power BI with Databricks SQL.
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| # | Folder | Description |
|---|---|---|
| 01 | Connection Parameters | Using Power BI parameters to efficiently manage connections to Databricks SQL |
| 02 | DirectQuery-Dual-Import | Using different storage modes - Direct Query vs Dual vs Import |
| 03 | Logical Partitionoing | Improving data refresh performance with Power BI partitioning |
| 04 | Query Parallelisation | Improving performance of Power BI Reports in Direct Query mode using query parallelisation |
| 05 | User-defined aggregations | Improving performance of Power BI reports using User-defined aggregations |
| 06 | Dynamic M Query Parameters | Using Dynamic M Query Parameters for better control over SQL-query generation and performance optimization |
| 07 | Query optimization using PK | Query optimization using primary key constraints |
| 08 | Automatic aggregations | Improving performance of Power BI reports using Automatic aggregations |
| 09 | Private Connections | Making private connections to the Databricks Workspace from the Power BI Service |
| 10 | Pushdown Calculations | Improve performance of DirectQuery and Composite models by pushing calculations down to Databricks SQL |
| 11 | Generated vs Persisted dimensions | Improve performance of DirectQuery and Composite models by using generated vs persisted dimension tables |