Data Warehouses and Data Mining

This article gives a detailed summary of the role of data warehouses and data mining, and their relationship to organizational databases. As you read, pay attention to how data warehouses are used to improve decision-making in organizations. Keep a summary in your notes of how an organization you are involved with could benefit from data mining and data warehousing.

Data Mining Life Cycle

Data mining operations require a systematic approach. The sequence of the phases is not strict and moving back and forth between different phases is always required. The general phases in the data mining process to extract knowledge are:

  1. Problem definition: This phase is to understand the problem and the domain environment in which the problem occurs.
  2. Creating a database for data mining: This phase is to create a database where the data to be mined are stored for knowledge acquisition.
  3. Exploring the database: This phase is to select and examine important data sets of a data mining database in order to determine their feasibility to solve the problem.
  4. Preparation for creating a data mining model: This phase is to select variables to act as predictors.
  5. Building a data mining model: This phase is to create multiple data mining models and to select the best of these models.
  6. Evaluating the data mining model: This phase is to evaluate the accuracy of selected data mining model.
  7. Deploying the data mining model: This phase is to deploy the built and the evaluated data mining model in the external working environment.