Dragon1 Open EA Method

1. A new view on EA

    2. Dragon1 Introduction

    3. EA in Practice

    4. Way of Thinking

    5. Way of Working

    6. Way of Representing

    7. Way of Supporting















    Data Mining Definition

    What is Data Mining

    Data mining is the process of finding patterns and opportunities in very large sets of data and take 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 databases.

    Data Mining Examples

    Some well-known example of data mining are:

    • Grouping data on webshops can be very hard to do. What groups to choose? With data mining, one can see based on user search data what the groups are 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 human DNA sequence and the variability in disease susceptibility.

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    Data Mining spotting opportunities using big visualizations.

    More examples of data mining here.