Data Warehousing Course outline - University of Sargodha

Course Title: Data Warehousing

Course Code: CS-4441

Course Structure: Lectures: 3 / Labs: 0

Credit Hours: 3

Prerequisites: CMP-3450 (Database Systems)

Course Syllabus:

Introduction to Data Warehousing, Data Warehouse System Lifecycle, Analysis and
Reconciliation of Data Sources, User Requirement Analysis, Conceptual Modeling, Conceptual
Design, Workload and Data Volume, Logical Modeling, Logical Design, Data-staging Design,
Indexes for the Data Warehouse, Physical Design, Data Warehouse Project Documentation, Case
Studies, Tools for Data Warehousing: MS SQL and Teradata.

Course Outline:

1.      Introduction to Data Warehousing: Brief History, Characteristics, Architecture, Data
Staging and ETL, Multi-dimentional Model, Meta-data, Accessing Data Warehouse,
ROLAP, MOLAP, and HOLAP. [TB1: Ch. 1]

2.      Data Warehouse System Lifecycle: Risk Factors, Top-Down vs Bottom-Up, Data Mart
Design Phases, Methodological Framework - Data-Driven, Requirement-Driven; Testing
Data Marts. [TB1: Ch. 2]

3.      Analysis and Reconciliation of Data Sources: Inspecting and Normalization Schemata,

Integration Problems, Integration Phases, Defining Mapping. [TB: Ch. 3]

4.      User Requirement Analysis: Interviews, Glossary-based Requirement Analysis,
Additional Requirements. [TB: Ch. 4]

5.      Conceptual Modeling: Dimensional Fact Model, Events and Aggregation, Temporal
Aspects, Overlapping Fact Shcemata, Formalizing the Dimensional Fact Model. [TB: Ch.
6]

6.      Conceptual Design: ER Schema-based Design, Relational Schema-based Design, XML
Schema-based Design, Mixed-approach Design. Requirement-driven Approach Design.
[TB: Ch. 6]

7.      Workload and Data Volume [TB1: Ch. 7]

8.      Logical Modeling: MOLAP and HOLAP Systems, ROLAP Systems, Views, Temporal
Scenarios. [TB1: Ch. 8]

9.      Logical Design: From Fact Schemata to Start Schemata, View Materialization, View
Fragmentation. [TB1: Ch. 9]

10. Data-staging Design: Population Reconciled Databases, Cleansing Data, Populating
Dimensional Tables, Populating Fact Tables, Populating Materialized View

11.  Indexes for the Data Warehouse: B*-Tree Indexes, Bitmap Indexes, Projection Indexes,
Join & Star Indexes, Spatial Indexes, Join-Algorithm. [TB1: Ch. 11]

12. Physical Design: Optimizers, Index Selection, Splitting a Database into Tablespaces,
Allocating Data Files, Disk Block Size. [TB1: Ch. 12]

13. Data Warehouse Project Documentation: Data Warehouse Levels, Data Mart Level, Fact
Level

14.  Case Studies, Tools for Data Warehousing: MS SQL and Teradata
Textbook(s):

•         Data Warehouse Design: Modern Principles and Methodologies by Matteo Golfarelli
and Stefano Rizzi, McGraw-Hill Osborne Media; 1^st Edition (May 26, 2009). ISBN-10:
0071610391

Reference Material:

•         Building the Data Warehouse by William H. Inmon, Wiley; 4^th Edition (2005). ISBN-10:
0764599445

•         The Data Warehouse Lifecycle Toolkit : Expert Methods for Designing, Developing, and
Deploying Data Warehouses by Ralph Kimball, Laura Reeves, Margy Ross and Warren
Thornthwaite, Wiley (August 13, 1998). ISBN-10: 0471255475

•         Data Warehousing Fundamentals for IT Professionals by Paulraj Ponniah, Wiley; 2^nd
Edition (2010). ISBN-10: 0470462078

•         Data Mining and Data Warehousing: Practical Machine Learning Tools Techniques by
Ram Kumar Singh and Amit Asthana, LAP LAMBERT Academic Publishing (2012).
ISBN-10: 3659118419

Note: This content is obtained from official documents of University of Sargodha and applied on BS Computer Science for Main Campus, Sub Campuses, and Affiliated Colleges.