Hi @pmscorca
Thanks for using Microsoft Fabric Community.
OneLake in Fabric is a Data Lake as a Service solution that provides one data lake for your entire organization, and one copy of data that multiple analytical engines can process. OneLake for Microsoft Fabric is automatically provisioned the first time you create a specific type of data item within Fabric. Creation of OneLake (though it happens automatically) in scenarios where you want to leverage Fabric's data storage and management capabilities for various data workloads.
Here are some specific scenarios:
Building a Lakehouse: If you plan to use Fabric to build a lakehouse environment for storing and managing raw and processed data for data scientists and analysts, OneLake will be created in the background to serve as the central storage for your lakehouse.
Working with Large Datasets: If you're dealing with big data sets that require scalable storage and efficient data access, Fabric's integration with OneLake provides a good solution. OneLake can handle large datasets efficiently. Centralized Data Governance: If your organization needs a centralized way to govern and manage its data across different teams and projects, Fabric with OneLake offers a unified platform. OneLake ensures all data is stored in a single location with access controls and governance policies.
Standardization and Cost Reduction: If your organization struggles with data silos and duplicated data storage across various systems, Fabric with OneLake can help. OneLake promotes a single source of truth for your data, reducing redundancy and storage costs. In simpler terms, any scenario where you use Fabric to store, manage, and process data sets likely involves OneLake working behind the scenes. It acts as the foundation for Fabric's data storage functionality.
For more details please refer : What is OneLake in Microsoft Fabric? – Data Ascend (data-ascend.com)
: What is OneLake in Microsoft Fabric ? (youtube.com)
I hope this information helps. If you any further queries, please do let us know.
Thank you.
