Registry

Module Specifications

Current Academic Year 2012 - 2013
Please note that this information is subject to change.

Module Title	Info. Systems - Spreadsheets & Data Modelling
Module Code	IS304
School	DCUBS
Online Module Resources
Module Teacher	Des McLaughlin
NFQ level	8	Credit Rating	5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

Description

Spreadsheet models have become an essential tool for business with applications in every business function and process. The aim of this module is to learn how to develop reliable and effective quantitative spreadsheet models and to use them appropriately to support analysis and decision-making for common business problems

Learning Outcomes

1. Discuss the role of spreadsheets to assist analysis and decision-making in different functions - operations, finance, marketing, etc.
2. Discuss the benefits, limitations, and risks of spreadsheet models in organizations
3. Appraise the value, relevance, and usefulness of data sources to underpin the reliability of a model
4. Select and apply the appropriate Excel function for particular applications and contexts
5. Evaluate and discuss best practice in spreadsheet design, development, and use in organizations
6. Construct a spreadsheet model using MS Excel according to best practice

Workload	Full-time hours per semester
*Type*	*Hours*	*Description*
Lecture	10	A lecture will present the essential ideas and core concepts pointing students towards resources where they can get further information. Students are expected to prepare for each lecture by, for example, reading materials suggested by the lecturer.
Lecturer supervised learning	10	Assistance in the computer laboratory on aspects of spreadsheeet model development
Independent learning	55	Students are expected to study the recommended textbooks and journal articles, and are encouraged to read further around the topics in each module. Such private study will include preparation for specific classes â€“ for example to discuss a case, and other study related to assignments or to consolidate the material from lectures
Assignment	50	Students will be asked to prepare spreadsheet models
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.
Introduction to spreadsheets, their features, functions and operators.

Spreadsheet applications.
Modelling common business problems and using spreadsheets for analysis and decision-making in finance, operations, marketing, etc..

Data and information for models.
Data sources and their value.

Model planning and development.
Model structure, data, assumptions, flow, formulae, output.

List and data management,.
Excel data sort, filter and data functions, pivot tables.

Presenting information.
Charts, documentation and presentation.

Tools for sensitivity analysis and scenario development.
What-if, goal seek, optimisation, scenarios.

Larger models.
Lnking and referencing 3-D worksheets.

Spreadsheet modelling best practice.
Characterisation of spreadsheet models, and good practice in model design, development and use (Read & Batson approach).

Spreadsheet model risks and errors.
Characterising and preventing errors. Model quality; reviewing and auditing models.

Assessment Breakdown
Continuous Assessment	70%	Examination Weight	30%

Course Work Breakdown
Type	Description	% of total	Assessment Date
Project	Students will be asked to constuct a spreadsheet model according to given criteria	20%	Week 6
Project	Students will be asked to design and construct a spreadsheet according to given criteria and meeting best practice for design, build, and test.	50%	Sem 1 End

Reassessment Requirement
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