Business Intelligence and Data Warehousing


Course lecturer:               Denis Ssebuggwawo

Teaching Assistant(s):      Moses Wanjala and Sauya Zawedde

Pre-requisite(s):               Introduction to Relational Databases and SQL

Consultation hours:          Wednesday: 3.00 – 5.00 p.m. (Course Lecturer), Tuesday: 3.00 – 5.00 p.m. (TAs) [or by appointment by E-mail]

Lecture schedule:            Thursday: 2.00 – 5.00 p.m. (Day), 5.00 – 8.00 p.m. (Evening), Sunday: 11.00 – 2.00 p.m. (Weekend)


SUMMARY

Business Intelligence and Data Warehousing (BIDW) course aims to impart both theoretical knowledge and practical skills to students about business intelligence  (BI) and data warehousing (DW) concepts. The course identifies business drivers for business intelligence and technology drivers for data warehousing. The course provides an overview of uses and users of business intelligence and the associated applications that may be deployed. It also gives an introduction to data integration and data warehousing and its relation to business intelligence implementations. The course uses practical examples to illustrate technical & theoretical concepts, techniques as well as functions needed for successful implementation of BI and DW applications. At the end of the course, the student should be able to model enterprise data, develop associated BI applications and its supporting DW.

OBJECTIVES

At the end of the course, students should be able to:

  1. Describe the concepts, terminology and processes of BI and DW
  2. Define the basic concepts of BI and DW
  3. Describe the Data Integration Framework (DIF)
  4. Identify BI and DW uses, users and applications
  5. Describe BI and DW development processes
MODULES & LECTURE SLIDES

The course has the following major topics:

  1. Introduction to BI and DW
  2. BI and DW Architectures
  3. Data and Information Architectures
  4. Technology and Product Architectures
  5. Data Integration Framework
  6. Data Store Components, Data and Information Modeling
  7. Introduction to Data Analysis and Data Mining (Practical)
  8. Development of DW using MySQL (Practical)

The details are found in the course outline. Lecture Slides are given in the table below.

Lecture 1Introduction Business Intelligence and Data WarehousesLecture 7Dimensional Schemas: Star, Snow-flakes and Constellation
Lecture2 Business Intelligence and Data Ware houses ArchitecturesLecture 8Data Warehouse Design and Set-up: Tier Architectures
Lecture3 OLTP and OLAP ArchitecturesLecture 9 
Lecture 4Data and Information Architectures, Uses and Users of BI/DWLecture10  
Lecture 5Data Stores, Data Marts and CubesLecture 11 
Lecture6Dimensional Modeling Concepts:Dimensional and Fact TablesLecture12  
TEACHING & ASSESSMENT

Lectures Notes and/or Hand-outs and practical sessions. At least 3 tests (10%) and 4 assignments (15%), Group Presentations /Practicals (10%),

Class Attendance (5%) which will contribute for 40% of the final assessment and the remaining 60% will be in form of a three-hour examination.

[2 hours-Theory, 1 hour working on class assignment]

REFERENCES & RESOURCES

Course Text Books:

  1. The Data Warehouse Toolkit by Ralph Kimball – John Wiley & Sons Publications.
  2. Building a Data Warehouse: with Examples on SQL Server by Vincent Rainardi

References:

  1. Decision Support in the Data Warehouse by Paul Gray, Hugh J. Watson – Prentice Hall.
  2. Dimensional Data Warehousing with MySQL: A Tutorial by Djoni Darmawikarta
  3. Microsoft data Warehouse Toolkit: With SQL Server 2005 and the Microsoft Business Intelligence Toolset by Joy Mundy, Warren Thornthwaite, and Ralph Kimball
  4. Oracle 10g Data Warehousing by Lilian Hobbs, Susan Hillson, Shilipa Lawande and Pete Smith
ASSIGNMENTS/TEST, LAB SESSIONS & GROUP DISCUSIONS
AssessmentDue DateSolutions
Assignment 1
Assignment 2
  
Test 1
Test 2
  
Lab Session 1
Lab session 2
  
Group 1
Group 2
  
EXAMS

Past Sample Questions are found here.

GRADES

Assignments, test, lab session and group discussion results