Module Details

Module Code: DATA_1
Module Title: Data Analytics
Title: Data Analytics
Module Level:: 8
Credits:: 5
Module Coordinator: Janette Davies
Module Author:: Owen Brady
Domains:  
Module Description: Use data gathering, organisation and analysis techniques to gain greater insight to customer needs and personalise the user experience based on customer profiles.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Create a database application using advanced query and reporting techniques using an end user database tool.
LO2 Develop and analyse databases using Structured Query Language (SQL) using efficient query techniques.
LO3 Analyse data from web analytics and public datasets using appropriate technologies.
LO4 Appreciate the strategic context of contemporary information systems within an organisation.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is recommended before enrolment in this module.
No recommendations listed
Co-requisite Modules
No Co-requisite modules listed
Additional Requisite Information
No Co Requisites listed
 
Indicative Content
Data Analysis
Database tools for work with customer data sets. Design a relational database using entity modelling, keyed relationships. Advanced queries for database mining using query authoring in a DBMS end user tool select, joins, grouping, aggregates, parameter. Developing a suite of management reports to assess organisational performance using a DBMS end user tool.
Structured Query Language (SQL)
select, joins, grouping, aggregates, distinct, ordering - all relevant query tool to extract and analyse data using SQL.
Personalisation & Web-analytics
User/customer focused design & user experience Consistent personalisation across channels Recommendation systems & collaborative filtering Implementing web analytics Interpreting web metrics to tune content and user experience The ethical use of user data in personalisation systems
Information Systems for Management
"Three Era" model, data vs. information vs. knowledge, management information systems classification, strategic alignment. New areas in data management e.g. object-oriented databases, noSQL databases, big data, blockchain, public ledgers. Disintermediation of traditional business finance models with De-Fi.
Module Content & Assessment
Assessment Breakdown%
Continuous Assessment100.00%

Assessments

Full Time

Continuous Assessment
Assessment Type Case Studies % of Total Mark 50
Timing n/a Learning Outcomes 1,2,4
Non-marked No
Assessment Description
Group project where teams develop web enabled data systems that are one of
• Customer relationship management systems.
• Transaction Processing Systems
• Knowledge Management Systems
• Decision Support Systems

Individuals are asked to justify aspects of the system in the strategic context of the organisation and rate the system in the different classifications of the Three Era Model

During this project students’ performance using agile methodology of delivering on milestones buddy work etc. is assessed.
Assessment Type Practical/Skills Evaluation % of Total Mark 50
Timing n/a Learning Outcomes 3,4
Non-marked No
Assessment Description
Students are given access to a website with web analytics installed – they are asked to analyse the data and make suggestions on improvement of structure, content and personalisation.

Students are asked to discuss whether the data would best be stored in relational databases or more modern databases or public ledgres.
No Project
No Practical
No End of Module Formal Examination

SETU Carlow Campus reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Workload Category Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Practicals Contact Data Analytics 12 Weeks per Stage 4.00 48
Independent Learning Non Contact Data Analytics 15 Weeks per Stage 6.00 90
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Workload Category Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Data Analytics 12 Weeks per Stage 2.00 24
Independent Learning Time Non Contact Reading, research and assessment preparation 15 Weeks per Stage 4.00 60
Total Weekly Contact Hours 2.00
 
Module Resources
Recommended Book Resources
  • Michael Alexander,Richard Kusleika. (2018), Access 2019 Bible, 1. John Wiley & Sons, p.1296, [ISBN: 9781118490358].
Supplementary Book Resources
  • Connolly, T. & Begg, C.. (2004), Database Systems: A Practical Approach to Design, Implementation and Management, 4th. Addison-Wesley, Harlow, [ISBN: 9780321210258].
  • Joel J. Davis. (2018), Google Analytics Demystified, 4th. CreateSpace, p.736, [ISBN: 9781514858240].
Recommended Article/Paper Resources
Supplementary Article/Paper Resources
  • Taylor & Francis. Journal of Management Information Systems.
Other Resources
Discussion Note: