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DATA WAREHOUSING AND DATA MINING

DATA WAREHOUSING AND DATA MINING

DATA WAREHOUSING AND DATA MINING. S. Sudarshan Krithi Ramamritham IIT Bombay sudarsha@cse.iitb.ernet.in krithi@cse.iitb.ernet.in. Course Overview. The course: what and how 0. Introduction I. Data Warehousing II. Decision Support and OLAP III. Data Mining IV. Looking Ahead

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1.99k views • 169 slides
DATA WAREHOUSING AND DATA MINING

DATA WAREHOUSING AND DATA MINING

DATA WAREHOUSING AND DATA MINING. Course Overview. The course: what and how 0. Introduction I. Data Warehousing II. Decision Support and OLAP III. Data Mining IV. Looking Ahead Demos and Labs. 0. Introduction.

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3.1k views • 169 slides
DATA WAREHOUSING AND DATA MINING

DATA WAREHOUSING AND DATA MINING

DATA WAREHOUSING AND DATA MINING. Which are our lowest/highest margin customers ?. Who are my customers and what products are they buying?. What is the most effective distribution channel?. What product prom- -otions have the biggest impact on revenue?.

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1.27k views • 109 slides
Technologies of the future

Technologies of the future

Technologies of the future. S. Sudarshan Dept. of Computer Science & Engg. IIT Bombay. Where is the IT industry heading to?. Internet technologies E-Commerce Web databases, XML, etc Data Warehousing Data mining. What is common amongst them?. Data intensive applications.

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629 views • 39 slides
DATA WAREHOUSING AND DATA MINING

DATA WAREHOUSING AND DATA MINING

DATA WAREHOUSING AND DATA MINING. Mubarak Banisakher. Course Overview. The course: what and how 0. Introduction I. Data Warehousing II. Decision Support and OLAP III. Data Mining IV. Looking Ahead Demos and Labs. 0. Introduction.

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669 views • 36 slides

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