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SIS 3204 Business Intelligence & Data Warehousing

Course Outline

Pre-requisite Courses: An Introductory Course on Databases and SQL

Course Description

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 it’s supporting DW.

Course Objectives:

At the end of the course the student should be able to:

  • Describe the concepts, terminology and processes of BI and DW
  • Define the basic concepts of BI and DW
  • Describe the Data Integration Framework (DIF)
  • Identify BI and DW uses, users and applications
  • Describe BI and DW development processes
  • Describe data, BI and DW (OLAP) architectures
  • Model data and information of an enterprise for BI and DW [9 hrs ]
  • Design a DW

Course Content

1.  Introduction to BI and DW
  • Brief History: Data analysis and reporting
  • BI defined
  • DW defined
  • Business drivers for BI Business drivers for DW
  • Applications that use BI and DW.

[6 hrs ]

2.  BI and DW Architectures
  • The four architectures: Data, Information, Technology and Product OLAP architectures
  • Relationship between BI and DW

[3 hrs ]

3.  Data and Information Architectures
  • Data modelling concepts
  • Data Integration Framework (DIF) Business applications of BI
  • OLAP Architectures
  • Uses and users of BI and DW
  • Processes, data stores and data architectures
  • Data warehouse, data mart, cubes

[6 hrs ]

4.  Technology and Product Architectures
  • Data integration Databases Business intelligence DW deployment and operational tools
  • BI and DW vendors

[6 hrs ]

5.  Data Integration Framework
  • Architectures, processes and data stores Standards,
  • Tools and Skills Data filtering, summarization and aggregation
  • Data modelling and data profiling

[6 hrs ]

6.  Data Store Components, Data and Information Modeling
  • Data modelling concepts: conceptual, logical and physical models Entity-Relationship (ER) modelling and object-role modelling (ORM)
  • Data structure options: star, snowflake, normalized (3NF) and de-normalized
  • Metadata: technical, business, process

[6 hrs ]

7. Introduction to Data Analysis and Data Mining (Practical)

  • Data analysis with DB2
  • OLAP Data mining with DB2 intelligent miner for data
  • Process step control for with DB2 Warehouse Miner

[6 hrs]

8. Development of DW using MySQL (Practical)   [12 hrs]

Course Delivery, Assessment and Grading

 Course Delivery: The course will consist of lectures, self-study hand-outs, group presentations and/or tutorials.

Course Assessment and Gradin: The assessment of the course is broken as follows:

Assessment:
Hand-in Assignments (Best 2)
(%) 15 
Tests (Best 2)10
Group Presentations (Practical)10
Class Attendance5
Sub-total: 40
Final Exam60 
Sub-total: 60
Total: 100%

Course Main Texts

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

Additional References

  1. Decision Support in the Data Warehouse by Paul Gray, Hugh J. Watson – Prentice
  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

 

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