| Feature | Data Warehouse | Data Mart | Data Lake |
|---|---|---|---|
| Data Type | Processed & Structured | Processed & Structured (subset of DW) | Raw, Unstructured & Semi-structured |
| Purpose | Enterprise-wide analysis & reporting | Department-specific analysis | Big Data, AI, ML, and storage |
| Storage | High-cost, optimized for querying | Lower-cost, faster for department use | Cheap storage, large-scale capacity |
| Data Processing | Transformed & cleaned | Transformed & cleaned (specific to department) | Raw, can be processed later |
| Best Use Case | Business Intelligence, Reports, Dashboards | Departmental reports (Sales, HR, Finance) | AI, Machine Learning, Real-time analytics |
| Example in Business | Amazon’s sales & customer data | Amazon’s marketing analytics | Netflix storing all user activity logs |
Monday, 30 June 2025
Difference Between Data Warehouse, Data Mart & Data Lake
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