KDD (Knowledge Discovery in Databases) means gaining knowledge from data volumes. It covers a more common data mining and a preparation analysis. The goal of the KDD is to recognise so far unknown relations in existing large data volumes.
As opposed to data mining,  KDD includes also the preparation of the data as well as the evaluation of results. The stages of KDD processes are:

  1. Collection of  background data for the business question
  2. Definition of the target for the analysis
  3. Data selection
  4. Data validation
  5. Data reduction (e.g. through transformations)
  6. Selection of a model, in which the found knowledge to be represented
  7. Data mining, own data analysis
  8. Interpretation of the obtained results
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