DATA MINING APPLICATION
WHERE DATA MINING CAN BE USED?
For example, data mining will be helpful for:
Actually, you will benefit from data mining if your assumptions are
related to data analysis and implementation of knowledge.
Use knowledge discovery for efficient opportunities identifying, sales
forecasting, marketing campaigns analysis, clients classification,
market researches, product positioning etc.
- analysts and managers who have to deal with strategic and tactical
- managers responsible for revenue and cost reduction
- risk managers in insurance, to minimise the risk of claims and to
maximise the profit
- educators, to improve educational processes, to conduct researches,
provide analysis of education effectiveness and institutional decisions
- scientists, to provide new knowledge for researches in various fields
Business intelligence benefits
Data mining enables companies, in the context of defined business objectives,
discover new knowledge, to explore, visualise and understand their data, and to
identify patterns, relationships and dependencies that impact on business
Various data mining techniques, like decision trees, decision rules (if-then),
etc, help to create effective models for decision making, making data
warehousing much more than just a method of data collecting.
Here are a few snapshots how data mining can benefit certain industries.
- Retail / Marketing
Identify buying behavior patterns from customers and model customer acquisition.
Find associations among customer demographic characteristics.
Predict which customers will respond to mailing.
Detect patterns of fraudulent credit card usage.
Identify "loyal" customers.
Predict customers that are likely to change their credit card affiliation.
Determine credit card spending by customer groups.
Find hidden correlations between different financial indicators.
Identify stocks trading rules from historical market data.
- Insurance and Health Care
Claims analysis - determine which medical procedures are claimed together.
Predict which customers will buy new policies.
Identify behavior patterns of risky customers.
Reduce losses through investigation of incidence of fraud.
Determine the distribution schedules among outlets.
Analyze loading patterns.
Characterize patient behavior to predict office visits.
Identify successful medical therapies for different illnesses.