Module Details
Module Code: |
DATA_1 |
Module Title:
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Data Analytics
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Title:
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Data Analytics
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Module Level:: |
8 |
Module Coordinator: |
Janette Davies
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Module Author:: |
Owen Brady
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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.
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Learning Outcomes |
On successful completion of this module the learner will be able to: |
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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.
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No recommendations listed |
Co-requisite Modules
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No Co-requisite modules listed |
Additional Requisite Information
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No Co Requisites listed
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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.
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Structured Query Language (SQL)
select, joins, grouping, aggregates, distinct, ordering - all relevant query tool to extract and analyse data using SQL.
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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
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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.
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Module Content & Assessment
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Assessment Breakdown | % |
Continuous Assessment | 100.00% |
AssessmentsFull Time
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 |
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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
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Recommended Book Resources |
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Michael Alexander,Richard Kusleika. (2018), Access 2019 Bible, 1. John Wiley & Sons, p.1296, [ISBN: 9781118490358].
| Supplementary Book Resources |
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Connolly, T. & Begg, C.. (2004), Database Systems: A Practical Approach to Design, Implementation and Management, 4th. Addison-Wesley, Harlow, [ISBN: 9780321210258].
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Joel J. Davis. (2018), Google Analytics Demystified, 4th. CreateSpace, p.736, [ISBN: 9781514858240].
| Recommended Article/Paper Resources |
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Harvard Press. Harvard Business Review,
| Supplementary Article/Paper Resources |
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Taylor & Francis. Journal of Management Information
Systems.
| Other Resources |
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Google Analytics,
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CIO.com,
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Microsoft Access Support,
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Andreessen Horowitz. a16z podcast,
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The Verge. Decoder with Nilay Patel,
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