Module Descriptor

15/08/2012

Code:

CE00405-5

Version:

3

Approval Status:

Valid Current

Title:

DATA MANAGEMENT

Section:

Computing, Engineering & Technology

Level:

5

Contact

E-mail Address

VLE

CLARE STANIER

[email-masked]

Blackboard

Pattern Of Delivery

Credits

15

Contact Hours

Independent Study Hours

Total Learning Hours

36

114

150

Description of Pattern of
Delivery

Pattern 1, study 100% in period
2

Site

STAFFORD

Registration Conditions

Module Version Condition Text

None

Module Details

Assessment Details

A COURSEWORK length 1500 WORDS weighted at 50%. An EXAM length 2
HOURS weighted at 50%.

Examination 2 hours (50%) (Learning
outcomes 1, 2 and 3)

Coursework (50%) (Learning outcome
4)
Individual essay (1500 words) researching current issues
concerning the use of data within organisations

Indicative Content

The module will focus on the following key data
areas:-

Data Mining and Decision Support Systems - topics to
include (not exhaustive): concepts, techniques, related disciplines
(e.g. OLAP etc.), classification, clustering.
Data Warehousing -
architecture, star scheme, tuning, loading, etc.
Customer
Relationship Management and Groupware
Quality of
Data

Learning Strategies

Delivery of the module is as follows:
1 x 1 hour lecture per
week for the whole group
1 x 1 hour seminar style lecture to
encourage discussion and development of issues
1 x 1 hour
tutorial per week in groups of no more than 20 students
(1:n)2
(1:20)1

The following learning strategies will be
applied:
- Keynote lectures introducing the main points for the
topics covered by the core course material
- Student-centred
workshops/tutorials to develop and underline the main topics
introduced in the lectures
- Discursive sessions drawing on
practical examples

Students will also be encouraged to
develop their intellectual, communicative and problem solving
skills.

Prospectus Information

The module introduces techniques for utilising data once it has
been recorded in the database. The modules focuses on Customer
Relationship Management (CRM), Data mining, Data warehousing and
improving the quality of data.

Resources

Students will be provided with a Module Handbook including the
descriptor, schedule of delivery and additional reference material
to support student-centred study.
Additional case study material
and practical workbooks will be provided when appropriate to the
schedule.
Lecture notes will be provided electronically prior to
delivery and be available throughout the running of the
course.
Access to a PC with suitable word processing, diagramming
and appropriate tools for use in the producing the coursework and
supporting the practical workshops.

Special Admissions Requirements

None

Texts

Data Mining - Introductory and Advanced Topics, Dunham, 2002,
Prentice Hall, ISBN 0-13-088892-3
Oracle DBA Guide to Data
Warehousing and Star Schemas- Scalzo, 2003, Prentice Hall, ISBN
0-13-032584-8

Learning Outcome

1. DESCRIBE AND EVALUATE SYSTEMS TO AID DECISION SUPPORT

Knowledge & Understanding

2. IDENTIFY AND DESCRIBE KEY APPLICATION DOMAINS FOR DATA MINING
AND DATA WAREHOUSING

Analysis

3. DISCUSS AND REFLECT UPON THE EFFECT OF DIFFERENT CUSTOMER
RELATIONSHIP MANAGEMENT (CRM) SYSTEMS

Reflection

4. DEMONSTRATE AND DISCUSS THE APPLICATION OF DATA
MANAGEMENT IN A REAL WORLD CONTEXT

Problem Solving

Reflection