Module Code - Title:
MG4087
-
DEVELOPING BUSINESS ANALYTICS WORKFLOWS
Year Last Offered:
N/A
Hours Per Week:
Grading Type:
N
Prerequisite Modules:
Rationale and Purpose of the Module:
This module will allow students to understand how analytics can provide insights to support decision making for businesses. Using open source analytics software it will provide a no-code low-code way for students to develop quantitative skills as they interact with large, publicly available, datasets in order to develop actionable and sustainable insights for senior managers. The module is an introductory module on the use of analytics to support business decision making.
Syllabus:
Exploring open source datasets; selecting appropriate data; integrating data from multiple sources; applying analytics techniques relevant for business applications including market basket analysis, decision trees, cluster analysis, sentiment analysis and social network analysis; ethical implications of analytics; using analytics to generate insights and appropriate courses of action that can be implemented sustainably.
Learning Outcomes:
Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)
On successful completion of this module, students will be able to:
Integrate data from multiple sources.
Develop analytics workflows to analyse data.
Apply appropriate analytics techniques to datasets.
Interpret the value of reports generated using analytics techniques
Affective (Attitudes and Values)
On successful completion of this module, students will be able to:
Reflect on the ethical implications that arise when using analytics techniques.
Psychomotor (Physical Skills)
N/A
How the Module will be Taught and what will be the Learning Experiences of the Students:
The module will be taught through a combination of lectures and labs. The module will focus on integrating data, building workflows and identifying and applying analytics techniques while analysing the sub. Students will be expected to develop communication skills through participation in in-class discussion and debate on the strengths and weaknesses of various analytical techniques and their applicability to a range of business problems. Students will be expected to proactively manage their learning experience and develop skills in independent learning. Relevant, up to date research on analytics techniques will be integrated into the module. The module will be assessed using a range of tools including group projects and continuous assessment which will assess students technical, problem solving and communication skills.
Prime Texts:
Huntsinger R., (2025)
Business Analytics: Methods and Cases for Data-Driven Decisions
, Cambridge University Press
Other Relevant Texts:
Abdey J., (2023)
Business Analytics: Applied Modelling and Prediction
, SAGE Publications
Programme(s) in which this Module is Offered:
BACHELOR OF BUSINESS STUDIES
Semester(s) Module is Offered:
Spring
Module Leader:
john.walsh@ul.ie