In Microsoft Fabric, which component is used for integrated data storage and processing?

In Microsoft Fabric, which component is used for integrated data storage and processing?

• A. Lakehouse
• B. Dataflow
• C. Data lake storage
• D. Synapse

Answer: (A)

Lakehouse brings together storage and compute in one place. In Fabric, this means you store all your data—structured, semi-structured, and unstructured—within a single layer and can run analytics workloads directly on it, using tools like SQL and Spark, without moving data to a separate system. It also provides unified metadata, governance, and security, making integrated data storage and processing seamless. Dataflow handles data movement and transformations, not the storage/compute fusion. Data lake storage is the raw storage layer, not the processing capability. Synapse is another analytics platform, separate from this integrated approach in Fabric. So the component that provides integrated data storage and processing is the Lakehouse.

Lakehouse brings together storage and compute in one place. In Fabric, this means you store all your data—structured, semi-structured, and unstructured—within a single layer and can run analytics workloads directly on it, using tools like SQL and Spark, without moving data to a separate system. It also provides unified metadata, governance, and security, making integrated data storage and processing seamless. Dataflow handles data movement and transformations, not the storage/compute fusion. Data lake storage is the raw storage layer, not the processing capability. Synapse is another analytics platform, separate from this integrated approach in Fabric. So the component that provides integrated data storage and processing is the Lakehouse.