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Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title Data Warehousing and OLAP
Module Code CA270
School School of Computing
Module Co-ordinatorSemester 1: Mark Roantree
Semester 2: Mark Roantree
Autumn: Mark Roantree
Module TeachersMark Roantree
NFQ level 8 Credit Rating 5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None

A Data Warehouse is the model or structure that supports data mining and decision support through Online Analytical Processing (OLAP). This module teaches students how to construct Data Warehouses by understanding their structures and the concept of multi-dimensional modelling.

Learning Outcomes

1. Be able to build Data Warehouses for different application areas.
2. Be able to deploy the Data Warehouse Bus Matrix to create individual data marts.
3. Be able to design a multi-dimensional schema.
4. To understand the structures and functions that deliver OLAP for multi-dimensional schemas.
5. Be able to apply classification algorithms to mining data.
6. Be able to apply clustering algorithms to interpret data.
7. Be able to apply ARM algorithms in the area of data mining.

Workload Full-time hours per semester
Type Hours Description
Lecture24No Description
Assignment Completion50No Description
Independent Study51No Description
Total Workload: 125

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Introduction to Data Warehouses

Data Warehouse Architecture
ETL and System Components

Multidimensional Data Model
Data Cubes, Different schema types

Dimensional Design
4-step process to designing the data warehouse

Data Warehouse Deployment
Using the Data Warehouse Bus Matrix

Data Warehouse Implementation
Indexing OLAP and Data Cube Computation

Efficient Computation of Data Cubes
Algorithms and methods for efficient cube computation

Web Data Warehouses
Incoporating web generated data into the warehouse

Warehouse Case Studies
An examination of a number of Warehouse Implementations

Assessment Breakdown
Continuous Assessment20% Examination Weight80%
Course Work Breakdown
TypeDescription% of totalAssessment Date
AssignmentData Warehousing assignment, involving OLAP and star schema design.20%n/a
Reassessment Requirement Type
Resit arrangements are explained by the following categories;
1 = A resit is available for all components of the module
2 = No resit is available for 100% continuous assessment module
3 = No resit is available for the continuous assessment component
This module is category 1
Indicative Reading List

  • Han & Kamber: 0, Data Mining: Concepts and Techniques, 3 & 4, Morgan Kaufmann,
  • Kimball & Ross: 0, The Data Warehouse Toolkit, Wiley,
Other Resources

Programme or List of Programmes
DSBSc in Data Science
ECSAStudy Abroad (Engineering & Computing)
ECSAOStudy Abroad (Engineering & Computing)

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