About 13 - Data Warehousing and Mining

Data Warehousing and Mining (MIS601) is a specialized course that delves into the principles, technologies, and methodologies associated with data warehousing and data mining. The course explores the design and implementation of data warehouses, as well as techniques for extracting valuable insights and patterns from large datasets through data mining.

Program Learning outcome:

  • Understand the architecture and design principles of data warehouses, including data modeling and schema design.
  • Learn Extract, Transform, Load (ETL) processes for populating and updating data warehouses with relevant and high-quality data.
  • Gain practical skills in implementing and managing data warehouses using industry-standard tools and technologies.
  • Explore various data mining techniques, such as clustering, classification, association rule mining, and anomaly detection.
  • Develop the ability to recognize meaningful patterns, trends, and insights from large datasets.
  • Apply predictive modeling techniques to make informed decisions based on historical data and trends.
  • Learn strategies for optimizing data warehouse performance and scalability.
  • Utilize data visualization tools to effectively communicate findings and trends to non-technical stakeholders.


TextBook Name:

"The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling" by Ralph Kimball and Margy Ross.

Assessment Methods

Midterm Exam
30%
Final Project and Exam
70%