What is Data Mining?
Data mining is the process of finding patterns and opportunities in very large sets of data and taking action upon them. Methods used in Data Mining come from business analytics, artificial intelligence, machine learning, and statistics.
Data Mining is sometimes also seen as knowledge discovery in the databases in a data warehouse.
Data Mining Examples
Some well-known examples of data mining are:
- Grouping data on webshops can be very hard to do. What groups to choose from? With data mining, one can see based on user search data what the groups people tend to look for.
- Detecting groups' behavior in a certain part of a process. With data mining, you can answer the question: which 5 steps do most users take after signing up to the system?
- Data mining can help to reveal who the most successful and efficient employees are and which customers are the best clients.
Data Mining Techniques
Often used techniques in data mining are:
- Data mining software uses advanced pattern recognition algorithms to sift through large amounts of data. This assists in the discovery of unknown business information at a strategic level.
- Sequence mining is a technique used in Human Genetics to learn to understand the relationship between the inter-individual variations in the human DNA sequence and the variability in disease susceptibility.
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Data Mining as Solution spotting opportunities using big visualizations.
More Examples of data mining here on Wikipedia.
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