Registry

Module Specifications

Archived Version 2022 - 2023

Module Title
Module Code
School
Online Module Resources
NFQ level	8	Credit Rating	5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

Description

The module aims to equip students with an understanding of data analysis and visualisation techniques and the knowledge of a variety of tools and statistical techniques to make sense of the emergence and exponential growth of big data. It will teach students to identify suitable approaches for business related issues.

Learning Outcomes

1. Understand the data analysis pipeline, how it is used in organisations and the ethical implications.
2. Explain the purpose and benefits of data analysis, in particular the emergence of big data.
3. Understand the requirements for communicating data analysis through visualisations and critique both their own and other visualisations.
4. Use functions in spreadsheets such as import, filtering, manipulation, visualisation.
5. Identify and specify requirements (such as tools, data and organisational structure) for performing the analysis of complex business-related issues.

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	24	Lectures and in-class tutorials covering key topics of the course.
Laboratory	12	Laboratory hands-on experience running appropriate software.
Independent Study	89	Preparation for and reading after lectures.
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

Data analysis
big data, appropriate data selection processes, representative sampling, understanding requirements (data tools, organisation structures etc), using spreadsheets for analysis

Data visualisation
selecting appropriate graph types, making visualisations in spreadsheets, critiquing visualisations

Communication
design rules for visualisation, presenting data visualisations, report writing

Business process understanding
data analysis pipeline and how it is used in organisations

Assessment Breakdown
Continuous Assessment	%	Examination Weight	%

Type	Description	% of total	Assessment Date
Course Work Breakdown

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
Unavailable

Indicative Reading List

Few, Stephen: 2012, Show Me the Numbers, 2nd Ed., Analytics Press, 978-097060197

Other Resources

None

Programme or List of Programmes

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