![]() Just like every Office user can create a new Teams channel or SharePoint site without coordinating with the admin, OneLake enables similar distributed ownership through workspaces. This well-controlled system allows OneLake to be open to every user to add their own contributions to OneLake from every part of the organization without any friction. It establishes clear governance and compliance boundaries controlled by the tenant admin and all data in OneLake is governed by the tenant policies. The concept of a tenant is a unique benefit of a SaaS service. Governed by default with distributed ownership for collaboration OneLake is automatically available with every Fabric tenant with no additional resources to setup or manage. Each Fabric tenant will have exactly one OneLake where all the data of all the projects and for all the users will be stored. OneLake improves collaboration over a single organization wide data lake. One data lake for the entire organization A centralized OneLake data hub for data discovery and management.One security model living natively with the data in the lake (coming soon).One copy of data for use across multiple analytical engines.One data lake for the entire organization at scale.OneLake is the core of Fabric’s lake-centric approach. Just like organizations are using OneDrive for their documents, they now have OneLake for their data. OneLake is a complete, rich, ready-to-go enterprise-wide data lake provided as a SaaS service. Introducing Microsoft OneLake – “the OneDrive for Data”. The resulting data lake implementation is often a complex and hard to manage system, rife with both siloes and redundant data. And for all this to become usable for the business side, IT organizations must also build data warehouses, data marts, and cubes creating additional copies the lake data. To break down these silos, these organizations build additional complicated solutions with complex data movement to facilitate sharing and reuse. Data mesh patterns with independent business domain-driven lakes adds additional overhead and fragmentation with multiple teams managing their own siloed lake resources. Enterprise data lakes are mostly implemented as custom projects using raw storage covered with massive glue code designed to enable scalability, collaboration, compliance, security and governance. In reality, the vision is highly illusive. ![]() Organizations invest heavily in data lake strategies with the vision of having a central place to store all their data, break down silos, and simplify data blending, analysis, security, governance, and discovery. See Arun Ulagaratchagan’s blog post to read the full Microsoft Fabric preview announcement. Microsoft OneLake brings the first multi-cloud SaaS data lake for the entire organization
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |