Module Title:Data Analytics
Language of Instruction:English
Credits: 5
NFQ Level:8
Module Delivered In 1 programme(s)
Teaching & Learning Strategies: This subject is based in the computer lab. The class is first introduced to contemporary models for technology development.
Module Aim: 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 should be able to:
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.
Pre-requisite learning
Module Recommendations

This is prior learning (or a practical skill) that is recommended before enrolment in this module.

No recommendations listed
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed.
No requirements listed

Module Content & Assessment

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.
Assessment Breakdown%
Continuous Assessment100.00%
Continuous Assessment
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Case Studies 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. 1,2,4 50.00 n/a
Practical/Skills Evaluation 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. 3,4 50.00 n/a
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 Frequency Average Weekly Learner Workload
Practicals 12 Weeks per Stage 4.00
Independent Learning 15 Weeks per Stage 6.00
Total Hours 138.00
Workload: Part Time
Workload Type Frequency Average Weekly Learner Workload
Lecture 12 Weeks per Stage 2.00
Independent Learning Time 15 Weeks per Stage 4.00
Total Hours 84.00

Module Delivered In

Programme Code Programme Semester Delivery
CW_BWBUS_B Bachelor of Business (Honours) Options: in Business or Digital Marketing 8 Mandatory