Registry
Module Specifications
Archived Version 2022 - 2023
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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. | |||||||||||||||||||||||||||||||||||||
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 |
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Indicative Content and
Learning Activities Data analysisbig data, appropriate data selection processes, representative sampling, understanding requirements (data tools, organisation structures etc), using spreadsheets for analysisData visualisationselecting appropriate graph types, making visualisations in spreadsheets, critiquing visualisationsCommunicationdesign rules for visualisation, presenting data visualisations, report writingBusiness process understandingdata analysis pipeline and how it is used in organisations | |||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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Other Resources None | |||||||||||||||||||||||||||||||||||||
Programme or List of Programmes | |||||||||||||||||||||||||||||||||||||
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