What is the benefit of storing different layers of your lakehouse in separate workspaces?

• A. It can enhance security, manage capacity use, and optimize cost-effectiveness.
• B. It makes it easier to share data with colleagues.
• C. There's no benefit of storing different layers of your lakehouse in separate workspaces.
• D. It slows down data access but increases reliability.

Answer: (A)

Separating the different lakehouse layers into their own workspaces creates clear boundaries for security, resource management, and cost control. By assigning access controls to each workspace, you can ensure that only authorized users access raw data while analysts and applications interact with curated or analytics-ready data, strengthening data governance. Each layer can also scale compute independently, so heavy processing in the raw or bronze layer doesn’t impact queries on the curated layer, making capacity management more predictable. With separate workspaces, you can tailor budgets, quotas, and storage policies per layer, optimizing overall cost—moving or tiering data as needed and preventing one layer from driving up costs for the others. While sharing is possible, the primary benefit is the combination of stronger security, better control over compute and storage use, and improved cost efficiency.