2. Lots of collected and warehoused data being
Computer have become cheaper and more powerful
Competitive pressure
Data explosion problem
Starving for knowledge
Solution is data mining
3. Extraction of implicit, previously unknown and
potentially useful information from data
Exploration and analysis by automatic or semi
automatic means of large quantity of data
to discover meaning full pattern
4. What is data mining?
Data mining is knowledge discovery, extraction of
interesting non trivial, implicit, previously unknown
and useful information or pattern.
what is not data mining?
Expert system or statistical programs
Deductive query processing
5. Data base to be mined.
Relational, transactional, object oriented, time series,
etc..
Knowledge to be mined
Characterization, clustering, discrimination,
association, trend etc..
Techniques utilized
Data base oriented, data ware house(OLAP),machine
learning, statistics, neural network etc
Applications adapted
Retail, telecommunication ,banking, fraud detection,
market analysis etc
7. Data analysis and decision support
Market analysis
Risk analysis
Fraud detection
Text mining
Intelligent query answering
Sports
Astronomy
8.
9.
10.
11. Characterization and discrimination
Association
Classification and prediction
Cluster analysis
Outlier analysis
Trend and evaluation analysis
Statistical analysis
12. Mining methodology and user interaction
Performance and scalability
Issues relating to diversity of data types
Issues related to application and social impact
13. U.M. Fayyad, G.Shapiro,p.Smyth advances in
knowledgediscovery and datamining aaai/mit press1996
J.Han and m.Kamber datamining:concepts nad
techniques.Morgan kaufmann ,2000
https://www.simplilearn.com/data-mining.
http://searchsqlserver.techtarget.com/definition/data-mart.