Web and Data Mining Introduction
Data Mining: Introduction
Lecture Notes for Chapter 1
Introduction to Data Mining by Tan, Steinbach, Kumar
© Tan,Steinbach, Kumar
Introduction to Data Mining
4/18/2004
1
Why Mine Data? Commercial Viewpoint
O
Lots of data is being collected and warehoused
– Web data, e-commerce
– purchases at department/ grocery stores
– Bank/Credit Card transactions O
Computers have become cheaper and more powerful
O
Competitive Pressure is Strong
– Provide better, customized services for an edge (e.g. in
Customer Relationship Management)
© Tan,Steinbach, Kumar
Introduction to Data Mining
4/18/2004
2
Why Mine Data? Scientific Viewpoint
O
Data collected and stored at enormous speeds (GB/hour)
– remote sensors on a satellite
– telescopes scanning the skies
– microarrays generating gene expression data
– scientific simulations generating terabytes of data
O
O
Traditional techniques infeasible for raw data
Data mining may help scientists
– in classifying and segmenting data
– in Hypothesis Formation
Mining Large Data Sets - Motivation
O
O
O
There is often information “hidden” in the data that is not readily evident
Human analysts may take weeks to discover useful information Much of the data is never analyzed at all
4,000,000
3,500,000
The Data Gap
3,000,000
2,500,000
2,000,000
1,500,000
Total new disk (TB) since 1995
1,000,000
Number of analysts 500,000
0
1995
1996
1997
1998
1999
©From:
Tan,Steinbach,
R. Grossman,
Kumar
C. Kamath, V. Kumar,
Introduction
“Data Mining to Data for Mining
Scientific and Engineering Applications”
4/18/2004
4
What is Data Mining?
O Many
Definitions
– Non-trivial extraction of implicit, previously unknown and potentially useful information from data – Exploration & analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns
© Tan,Steinbach, Kumar
Introduction to Data Mining
4/18/2004
5
What is (not) Data Mining?
What is not Data
Mining?
O
O
What is Data
Lecture Notes for Chapter 1
Introduction to Data Mining by Tan, Steinbach, Kumar
© Tan,Steinbach, Kumar
Introduction to Data Mining
4/18/2004
1
Why Mine Data? Commercial Viewpoint
O
Lots of data is being collected and warehoused
– Web data, e-commerce
– purchases at department/ grocery stores
– Bank/Credit Card transactions O
Computers have become cheaper and more powerful
O
Competitive Pressure is Strong
– Provide better, customized services for an edge (e.g. in
Customer Relationship Management)
© Tan,Steinbach, Kumar
Introduction to Data Mining
4/18/2004
2
Why Mine Data? Scientific Viewpoint
O
Data collected and stored at enormous speeds (GB/hour)
– remote sensors on a satellite
– telescopes scanning the skies
– microarrays generating gene expression data
– scientific simulations generating terabytes of data
O
O
Traditional techniques infeasible for raw data
Data mining may help scientists
– in classifying and segmenting data
– in Hypothesis Formation
Mining Large Data Sets - Motivation
O
O
O
There is often information “hidden” in the data that is not readily evident
Human analysts may take weeks to discover useful information Much of the data is never analyzed at all
4,000,000
3,500,000
The Data Gap
3,000,000
2,500,000
2,000,000
1,500,000
Total new disk (TB) since 1995
1,000,000
Number of analysts 500,000
0
1995
1996
1997
1998
1999
©From:
Tan,Steinbach,
R. Grossman,
Kumar
C. Kamath, V. Kumar,
Introduction
“Data Mining to Data for Mining
Scientific and Engineering Applications”
4/18/2004
4
What is Data Mining?
O Many
Definitions
– Non-trivial extraction of implicit, previously unknown and potentially useful information from data – Exploration & analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns
© Tan,Steinbach, Kumar
Introduction to Data Mining
4/18/2004
5
What is (not) Data Mining?
What is not Data
Mining?
O
O
What is Data