This Presentation is about Data mining and its application in different fields. This presentation shows why data mining is important and how it can impact businesses.
4. Data Mining Contd…..
A data mining research carried out at supermarkets showed that,
Men who had children and who do shopping on Saturday to buy nappies for
their little ones tend to buy Beer also….
Interesting right?.....
Lets see some more examples……
6. Data mining Contd..
o Data mining in CRM
o Based on the behavior and personal
data about the customer, CRM
admisnitrter will divide the customer in
two classes.
o A Prediction model can be created using
this data to find the probability of losing
a customer in next two years.
7. Data Mining Contd..
IN CRM , it is a well known fact that acquiring a new customer cost 7 times
more than keeping the existing customer (churn prevention)
Thus CRM can help to reduce the churn rate
10. Why Data Mining
Terabytes of data generated every day
Abundance of data available from sources like business, society and science
Easy techniques of data collection ex: automated data collection tools,
database systems, computerized society etc
Need for analysis of massive data
11. What is Data Mining
It is a process of discovering
suitable
New
Potentially useful insights
Under stable patterns and trends in the large data sets
Using sophisticated mathematical algorithms
To segment the data
Evaluate the probability for future events
12. Stages of Data mining
Selection
•Segmenting the data according to criteria
•Example who have a car, people who are in govt jobs
Preprocessing
•Data cleansing stage, unnecessary information is removed
Transformation
. Data is transformed. Data is made usable and navigable
Data mining
. Stage of extracting of patterns from data
Interpretation and evaluation
•Patterns interpreted into knowledge that can be used to support human decision making,
13. Reasons for Data Mining popularity
Growing Data Volume
Limitations of Human Analysis
Low Cost of Machine Learning
15. Data Mining Process Model
Understanding
business
requirements
Deployment
Data collection
Data
Data prep and
analysis
Evaluation
Data modeling
16. Scope of Data Mining
Data Mining technology can generate new business opportunities
Automated prediction of trends and behaviors
Automated discovery of previously unknown patterns
Yield the benefits of automation on existing software and hardware platforms
Implemented on new systems as existing platforms are upgraded and new
products developed
17. Data Mining Limitations
Data mining systems relies on databases to supply the raw data for output.
Problem occurs as data bases tend to be dynamic, incomplete, noisy and large
Uncertainty
Size and updating problem
Limited information
18. Techniques used in Data Mining
Artificial Neural Networks
Decisions Trees
Genetic Algorithm
Nearest Neighbor Method
Rule Induction
19. Artificial Neural Networks
o System of interconnected neurons
that can compute values from
inputs by feeding information
through the network.
20. Decision Tree
Uses tree like model of decisions
and their possible consequences
23. Rule induction
The extraction of useful if-then rules from data based on
statistical significance.
24. Data Mining Application
Data mining techniques can be applied in various fields such as
Telecommunication
CRM
Banking
Medicine and Pharmaceuticals
Insurance
Management (Quality Assurance, Marketing)
Travel and Tourism..
25. Contd..
Media logistic
Academic Research
IT & ITES
Online Portals and Social Media Channels
Media and Advertising
Airline Companies
Sports
Finance
Film Industry and many more etc.
26. Contact Us
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Notas do Editor
Everything is sold and advertisedoninternext
Models inspired by animal CNS , that are capable of machine learning and pattern reorganization.
Decision support toolIncluding chance event outcomes, resource cost, utilityCommonly used in operation research, specifically decision analysis
mimics the process of natural evolutionbioinformatics, phylogenetics, computational science, engineering, economics, chemistry, manufacturing, physics etc..