Microsoft Fabric terms for a Data Engineer

1. OneLake: The unified data lake storage layer in Microsoft Fabric that serves as the single source of truth across the platform.

2. Lakehouse: A hybrid architecture in Fabric combining the benefits of data lakes and data warehouses, allowing both structured and unstructured data analysis.

3. Warehouse: A managed, scalable, SQL-based data warehouse experience within Microsoft Fabric designed for high-performance analytics.

4. Notebook: An interactive development environment in Fabric where you can write code in languages like PySpark, SQL, or markdown for data exploration and transformation.

5. Dataflow Gen2: A no-code/low-code ETL tool in Fabric used to ingest, transform, and load data using a graphical interface.

6. Power BI: The native reporting and visualization tool integrated with Microsoft Fabric, allowing for real-time data dashboards and reporting.

7. Semantic Model: A layer in Fabric where business logic and KPIs are defined, enabling users to analyze data consistently using tools like Power BI.

8. Pipeline: A data orchestration feature used to schedule and manage data workflows and ETL processes within Fabric.

9. Data Activator: A feature in preview that monitors data in real time and automatically triggers alerts or actions based on predefined conditions.

10. Capacity: Refers to the compute and storage resources allocated to a Microsoft Fabric workspace, often based on F SKU (e.g., F2, F4) for scaling performance.