The Process of Finding New Value in Existing Data

The "what" to "how" dimension makes the difference.

The Knowledge Discovery Associates process consists of five steps. Each step raises issues and questions about the outcome of the earlier steps. Thus, at each step, earlier stages are reviewed to achieve deeper understanding, which is measured on an extra dimension, called the "what" to "how" dimension.

The steps in the knowledge discovery process are:

Problem Specification. Starting with issues, concerns, and general objectives, a problem description evolves. This leads to a problem specification with quantifiable measures for later test and evaluation.

Business Context Representation. Background and contextual knowledge, prior practice, rules of operation, etc., are recorded and then encoded as computable objects.

Data Preparation. Phases include encoding the data dictionary and data field semantics, sample selection, and data cleaning. Technical issues addressed include missing data fields, data uncertainty, and ordering of events in time.

Data Analysis. Selection, application, integration, and customization of data mining and data analysis methods.

Presentation of Results. Test, validate, evaluate, implement, and report. Results must be provably novel, useful, and understandable.


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