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Aditi Sharma
Aditi Sharma

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πŸš€ Day 25 of My Python Learning Journey

Database vs Data Warehouse πŸ—„οΈ

Today I explored the key differences between Databases and Data Warehouses β€” two pillars of data management.

πŸ”Ή Database
β€’ Designed for day-to-day operations (OLTP – Online Transaction Processing).
β€’ Stores current data (e.g., banking, e-commerce).
β€’ Optimized for fast reads/writes.

πŸ”Ή Data Warehouse
β€’ Designed for analytics & reporting (OLAP – Online Analytical Processing).
β€’ Stores historical + integrated data from multiple sources.
β€’ Optimized for complex queries & aggregations.

πŸ“Œ Key Difference in One Line:

Database β†’ Running the business.
Data Warehouse β†’ Analyzing the business.

⚑ Fun Fact: The term Data Warehouse was first coined in the 1980s and became the backbone of business intelligence systems.

DataAnalytics #Database #DataWarehouse #100DaysOfCode #Python

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