Summary Data Mining and Data Warehouse important topics
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Module
Data Mining and Data Warehouse
Institution
Amrita University
Explore the world of data science with this in-depth document that covers essential topics like Data Science, Data Mining, Data Warehousing, and advanced clustering algorithms such as K-Means, K-Medoids, and the Apriori Algorithm. Whether you're a beginner or a professional, this guide will provide...
, What motivated Data Mining?
• Availability of huge amounts of data
• Need for turning such data into useful
information and knowledge that can be used
in various applications.
• We are drowning in data, but starving for
knowledge!
• It is a result of natural evolution of IT
, Evolution of DBS Technology
• 1960s:
– Data collection, Primitive file processing
• 1970s:
– Relational data model, relational DBMS implementation
• 1980s:
– RDBMS, advanced data models (extended-relational, OO, deductive, etc.)
– Application-oriented DBMS (spatial, scientific, engineering, etc.)
• 1990s:
– Data mining, data warehousing, multimedia databases, and Web databases
• 2000s
– Stream data management and mining
– Data mining and its applications
, Evolution of DBS Technology
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