People Innovation Excellence

DATA WAREHOUSE AND DATA MINING (4 Credits)

Learning Outcomes:

On successful completion of this course, students will be able to: Explain the basic concepts and architecture of data warehouse and data mining concepts and techniques; Analyze collection of data and techniques for pre-processing the data before using in data warehouse and data mining; Design data warehouse and data mining model; Analyze the strategy of design and implement data warehouse and data mining that appropriate to the need.

Topics:

  1. The Data warehouse Environment;
  2. The Data Warehouse and Design;
  3. The Data Warehouse and Technology;
  4. The Distributed Data Warehouse;
  5. External/Unstructured Data and the Data Warehouse;
  6. Data Warehouse Design and Building Review;
  7. Introduction/Overview of Data Mining;
  8. Getting to Know Your Data;
  9. Data Pre-processing;
  10. Classification: Basic Concepts – Decision Tree Induction;
  11. Classification: Basic Concepts – Rule-Based Classification;
  12. Classification: Basic Concepts – Bayes Classification Methods;
  13. Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods;
  14. Cluster Analysis: Basic Concepts and Methods;
  15. Data Mining Trends and Research Frontiers.

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