Microsoft Fabric Lakehouse
Microsoft Fabric is a data platform that employs the Lakehouse architecture. A Lakehouse is an approach that combines the best features of data lake and data warehouse technologies. This architecture provides more flexible, scalable, and performant data management by storing and processing different types of data in a single system.
Microsoft Fabric is a Lakehouse that uses Apache Spark and SQL computing engines for big data processing.
The Lakehouse is a unified platform that combines:
- The flexible and scalable storage of a data lakehouse.
- The ability to query and analyze data like a data warehouse.
The Lakehouse is presented as a database and is built on top of a data lake using Delta format tables. This structure combines the SQL-based analytical capabilities of a relational data warehouse with the flexibility and scalability of a data lake. Lakehouses can store all data formats and be used with various analytics tools and programming languages.
Use Cases:
- Big Data Analytics: Analyzing and processing large datasets.
- Machine Learning and Artificial Intelligence: Enabling data scientists and analysts to develop and deploy machine learning models.
- Data Integration: Integrating different data sources and consolidating them into a central data pool.
- Business Intelligence (BI): Visualizing and reporting data with business intelligence tools.
Advantages:
- Consolidation of data processing and analytics workloads onto a single platform.
- Flexibility to work with different data types.
- High-performance and scalable data management solutions.
- Advanced security and data management features.
Reference:
- Microsoft. (2024). Microsoft Fabric Analytics Engineer Course Materials. https://learn.microsoft.com/en-us/training/courses/dp-600t00
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