CS614 : Data Warehousing

Course Overview

Course Synopsis

The focal area of this course is to provide awareness of data warehouse basic components, importance of data warehouse in business, important steps and techniques to be considered during data warehouse development, and future trends and usage of data warehouse. This course will provide the knowledge and skills to design and implement a Data Warehouse. Presented in the regular lectures and 5 lab lectures, participants will experience all phases of a Data Warehouse implementation from Extract, Transform and Load (ETL) of the data to running queries on the final database. The course will have a look at OLAP, MOLAP, ROLAP and other systems and how they differ from one another. It will provide an understanding of how to use data warehousing techniques in implementing it on web.

Course Learning Outcomes

After completing this course you should be able to:

  • Design and implement a Data Warehouse
  • Define the basic concepts and importance of data warehouse
  • Identify the business areas where data warehouse is required
  • Use data warehouse for data mining projects


Course Calendar

TopicLectureResourcePage
Introduction To Data Ware Housing1, 2, 3, 4, 5Handouts10-40
Normalization6Handouts41-48
De-Normalization7Handouts49-53
De-Normalization Techniques8Handouts54-61
Assignment No. 1
Issues of De-Normalization9Handouts62-68
Online Analytical Processing (OLAP)10Handouts69-77
Multidimensional OLAP (MOLAP)11Handouts78-86
Relational OLAP (ROLAP)12Handouts87-97
Dimensional Modeling (DM)13Handouts98-108
Process Of Dimensional Modeling14Handouts109-118
Assignment No. 2
Issues Of Dimensional Modeling15Handouts119-128
Extract Transform Load (ETL)16Handouts129-139
Issues Of ETL17Handouts140-148
ETL Detail: Data Extraction & Transformation18Handouts149-157
Quiz No. 1
ETL Detail: Data Cleansing19Handouts158-164
Data Duplication Elimination & BSN Method20Handouts165-178
Introduction To Data Quality Management (DQM)21Handouts179-185
DQM: Quantifying Data Quality22Handouts186-192
Mid Term Exam
Total DQM23Handouts193-200
Need For Speed: Parallelism24Handouts201-211
Need Ffor Speed: Hardware Techniques25Handouts212-219
GDB
Conventional Indexing Techniques26Handouts220-230
Need For Speed: Special Indexing Techniques27Handouts231-238
Join Techniques28Handouts239-247
A Brief Introduction To Data mining (DM)29Handouts248-258
What Can Data Mining Do30Handouts259-268
Supervised Vs. Unsupervised Learning31Handouts269-282
DWH Lifecycle: Methodologies32Handouts283-288
DWH Implementation: Goal Driven Approach33Handouts289-298
Assignment No. 3
DWH Implementation: Goal Driven Approach34Handouts299-310
DWH Life Cycle: Pitfalls, Mistakes, Tips35Handouts311-320
Course Project36Handouts321-329
Case Study: Agri-Data Warehouse37Handouts330-339
Quiz No. 2
Case Study: Agri-Data Warehouse38Handouts340-347
Web Warehousing: An introduction39Handouts348-359
Web Warehousing: Issues40Handouts360-371
Lab Lecture-1: Data Transfer Service (DTS)41Handouts372-395
Lab Lecture-2: Lab Data Set42Handouts396-409
Lab Lecture-3: Extracting Data Using Wizard43Handouts410-435
Lab Lecture-4: Data Profiling44Handouts436-455
Lab Lecture-5: Data Transformation & Standardization45Handouts456-483
Final Term Exam
Note: This is tentative schedule and may subject to change
 
 
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