A data warehouse is a repository of information gathered from multiple sources and stored under a unified schema at a single site. So, a data warehouse is the database that stores current, historical and external data of potential interest to decision-makers through the company.

Data mining is one of the knowledge discovery tools that is used to analyze the huge volume of data contained in a data warehouse or data marts and to reveal the hidden patterns, trends or relationships in data.

Data Warehouse and Data Mining - Management Information System

In this “Data Warehouse and Data Mining - Management Information System” you will learn about following topics:

  1. Introduction of Data, Information, Field, Record, Table
  2. File System
  3. Database
  4. Objectives of the Database Approach
  5. Database System and Hierarchy
  6. Purpose of the Data Hierarchy
  7. Components of the Data Hierarchy
  8. Types of Database Model
  9. Database Management System
  10. Database Management System Tools
  11. Data Repository
  12. Data Warehouse
  13. Key Characteristics of Data Warehouse
  14. Types of Data Warehouse
  15. Pros of Data Warehouse
  16. Cons of Data Warehouse
  17. Knowledge Discovery in Database (KDD)
  18. Process of Knowledge Discovery in Database
  19. Need for a Data Warehouse
  20. Building a Data Warehouse
  21. Data Warehousing Technologies
  22. Online Analytical Processing (OLAP)
  23. Types of Online Analytical Processing
  24. Operations of Online Analytical Process
  25. Online Transaction Processing (OLTP)
  26. Difference between Online Analytical Processing and Online Transaction Processing
  27. Data Marts
  28. Meta Data
  29. Categories of Metadata
  30. Role of Metadata
  31. Data Warehouse Schema
  32. Data Mining
  33. Uses of Data Mining
  34. Data Mining Tools
  35. Data Mining Process
  36. Classification of Data Mining Algorithms
  37. Data Mining Techniques
  38. Implementation of Data Warehouse and Data Mining




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BCA 8th Semester Management Information System (MIS) Notes Pdf: