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Unit 10.8

Data Warehousing & Data Mining

IT 231: IT and Applications (BBA)

Data Warehousing 🗄️

A large, centralized repository of historical data collected from multiple sources, designed for query and analysis.

Integrated: Data from different systems is cleaned and unified.
Time-Variant: Retains historical data to analyze trends.
Non-Volatile: Once entered, data is not changed.

Data Mining ⛏️

The process of analyzing massive volumes of data to discover hidden patterns, correlations, and trends.

Uses AI, machine learning, and advanced algorithms.
Classification: Categorizing data.
Clustering: Grouping similar data without labels.
Association: Finding rules (e.g., "Customers who buy X also buy Y").

How They Work Together 🤝

The Data Warehouse provides the structured, clean data, and Data Mining provides the algorithms to extract actionable insights from it.

Mining requires a warehouse to avoid messy, fragmented data.
A warehouse is just storage without mining to unlock its value.

Thank You & Q&A