Knowledge discovery

Knowledge Discovery

KDD stands for Knowledge Discovery in Databases, which covers the creation of knowledge from structured and unstructured sources in an attempt to formalise the knowledge discovery process.

There are five steps:

  • Selection
  • Preprocessing
  • Transformation
  • Data Mining
  • Interpretation / Evaluation

CRISP-DM (CRoss Industry Standard Process for Data Mining) is another process to formalise the knowledge process. This time with six steps:

  • Business Understanding (Identify project objectives)
  • Data Understanding (Collect and review data)
  • Data Preparation (Select and cleanse data)
  • Modelling (Manipulate data and draw conclusions)
  • Evaluation (Evaluate model and conclusions)
  • Deployment (Apply conclusions to business)