The aim of this module is two-fold: (i) to provide the learner with an understanding of the creation, use and interpretation of tables and dashboards in a digital marketing context and (ii) to provide the learner with an understanding of databases with an emphasis on extracting data from databases.
Learning Outcomes
On successful completion of this module the learner will be able to:
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Learning Outcome Description
LO1
Create meaningful business related dashboards and reports in order to generate insight in a digital marketing context.
LO2
Describe databases and explain the difference between structured and unstructured data.
LO3
Construct SQL queries to manipulate data in a database.
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
Introduction to Databases
Database design, Big Data, structured and unstructured data.
Introduction to SQL
Simple select queries, nested queries, aggregate functions and table joins.
Dashboards
Create reports and dashboards using key software such as Tableau, Microsoft Excel, Google Data Studio, etc...
Extract Insight
Extract insight from dashboards and reports in a digital marketing context.
Module Content & Assessment
Assessment Breakdown
%
Continuous Assessment
100.00%
Assessments
Full Time
Continuous Assessment
Assessment Type
Examination
% of Total Mark
100
Timing
n/a
Learning Outcomes
1,2,3
Non-marked
No
Assessment Description Learners will be required to demonstrate achievement of the learning outcomes through continuous assessment. This work may take the form of a project (individual/group), practical exam, presentation but is not limited to these formats.
No Project
No Practical
No End of Module Formal Examination
Reassessment Requirement
Exam Board It is at the discretion of the Examination Board as to what the qualifying criteria are.
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
Practicals/labs
Every Week
3.00
3
Independent Learning
Non Contact
Independent learning
Every Week
6.00
6
Total Weekly Contact Hours
3.00
Workload: Part Time
Workload Type
Workload Category
Contact Type
Workload Description
Frequency
Average Weekly Learner Workload
Hours
Practicals
Contact
Practicals/labs
Every Week
1.50
1.5
Independent Learning
Non Contact
Independent Learning
Every Week
7.50
7.5
Total Weekly Contact Hours
1.50
Module Resources
Recommended Book Resources
Cole Nussbaumer Knaflic. (2019), Storytelling with Data, 1st. John Wiley & Sons, [ISBN: 9781119621492].
Steve Wexler, Jeffrey Shaffer, Andy Cotgreave. (2017), The Big Book of Dashboards, John Wiley & Sons, [ISBN: 1119282713].
Gordon Linoff. (2016), Data Analysis Using SQL and Excel, 2nd. John Wiley & Sons.
Lynn Beighley. (2007), Head First SQL, 3rd. O'Reilly Media, [ISBN: 9780596800857].
This module does not have any article/paper resources