Fabric foundations¶
Microsoft Fabric is a SaaS analytics platform that combines familiar Power BI, Azure Synapse Analytics, and Azure Data Factory experiences. It gives teams a shared data estate through OneLake while retaining specialized experiences for engineering, warehousing, science, real-time analytics, and reporting.
Workloads in the workshop¶
| Workload | Workshop relevance |
|---|---|
| Data Factory | Ingest and orchestrate data movement and transformation. |
| Data Engineering | Use Spark-based notebooks to prepare and transform data. |
| Data Warehouse | Query structured, curated data with SQL analytics. |
| Data Science | Train, evaluate, and register models with MLflow patterns. |
| Power BI | Build reports and semantic models from governed data. |
| Data Activator | React to data events with operational automation. |
OneLake and storage choices¶
OneLake reduces unnecessary data copies by providing a shared logical lake for the organization. In the workshop, use the lakehouse flow for raw-to-curated transformations; select warehouses where relational SQL reporting is the natural interface.
flowchart TB
O[Operational and external sources] --> F[Fabric ingestion]
F --> L[OneLake]
L --> LH[Lakehouse and Spark]
L --> WH[Warehouse and SQL]
LH --> BI[Power BI]
WH --> BI
Concepts to recognize¶
- Parquet and Delta: open table formats used for efficient analytical storage and reliable table operations.
- Shortcuts and mirroring: connect to data without treating every scenario as a full copy-and-paste migration.
- V-Order and Z-Order: storage and data-layout optimizations that can improve analytical performance for suitable workloads.
- Purview integration: governance, discovery, security, lineage, and compliance remain part of the data platform lifecycle.
See the source Fabric overview and Microsoft Fabric documentation for current product details.