Module Code - Title:
MN6152
-
APPLIED BUSINESS ANALYTICS
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 better 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.
Syllabus:
The module is an introductory module on the use of analytics to support business decision making. Content will include: 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. The module will also involve students using an open source analytics platform to conduct their analyses.
Learning Outcomes:
Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)
On successful completion of this module, students will be able to:
Gather and integrate suitable data for analysis.
Apply various analytics techniques to generate actionable insights to business and societal problems.
Evaluate the sustainability of the insights generated.
Develop and communicate recommendations to mention managers
Affective (Attitudes and Values)
On successful completion of this module, students will be able to:
Evaluate and reflect on the need to act responsibly and ethically when applying analytics to make decisions.
Psychomotor (Physical Skills)
On successful completion of this module, students will be able to:
How the Module will be Taught and what will be the Learning Experiences of the Students:
The module will be taught using a flipped classroom approach where the virtual learning environment will be used to enhance learning and help create an active learning environment. Lectures will be used to examine and discuss content and apply techniques to different problems. Computer laboratory sessions will provide the opportunity for students to develop practical skills in using an open source analytics platform to work on open source data. The module will get students to consider how to use analytics to generate insights (Curious GA, requiring the student to be inquisitive and engaged in problem-solving as well as developing the Agile GA where open-mindedness and adaptability are needed). Students will also develop sustainable and actionable insights (Courageous GA, requiring them to be innovative and enterprising). They will craft how to communicate their recommendations to senior managers (Articulate GA: necessitating inter-personal skills).
Research Findings Incorporated in to the Syllabus (If Relevant):
Prime Texts:
Abdey, J (2023)
Business Analytics: Applied Modelling and Prediction
, SAGE Publications Ltd
Asplen-Taylor, S (2022)
Data and Analytics Strategy for Business: Unlock Data Assets and Increase Innovation with a Results-Driven Data Strategy
, Kogan Page
Other Relevant Texts:
Various (2018)
HBR Guide to Data Analytics Basics for Managers (HBR Guide Series)
, Harvard Business Review Press
Programme(s) in which this Module is Offered:
MSMGNTTFA - MANAGEMENT
Semester(s) Module is Offered:
Spring
Module Leader:
john.walsh@ul.ie