BS4S48 - Strategic Business Analytics: Driving Decision Making 01 Sep 2024 - 31 Aug 2030 | Version 3
Associated Module Information
| Module Code: | BS4S48 | ||
|---|---|---|---|
| Module Title: | Strategic Business Analytics: Driving Decision Making | ||
| Faculty: | Faculty of Business and Creative Industries | ||
| Faculty Group: | Professional Development | ||
| Faculty Sub Group: | Professional Development | ||
| Module Leader: | Hai Nguyen | ||
| Module Team: | Claire Reed, Davina Evans, Andrew Thompson | ||
| First Intended Intake: | SEP 2024 | Final Year of Intake: | 2029 |
| Date Closed: | |||
| Credit Value: | 20 | Credit Level: | 7 |
| Language: | English | ||
| Percentage of Module Taught in Welsh: | 0 | ||
| Equivalent Module: | |||
| HECOS codes: | 100078 - business and management | ||
| HECOS Code Weighting: | 100 | ||
Document Version Information
| Version | 3 |
|---|---|
| Valid From | 01 Sep 2024 |
| Valid To | 31 Aug 2030 |
Module Aims
This module introduces the analytical methods required to understand, interpret, research, and manage complex data.
Upon completion of the module, students will be able to confidently draw insight from data and identify patterns and trends of interest for future exploration.
Additionally, students will develop the skills necessary to navigate through emerging and disruptive technologies within the context of business data, equipping them to adapt to evolving technological landscapes and leverage innovative tools for enhanced decision-making and strategic planning.
Content Summary
The module introduces fundamental concepts in Business Analytics, covering Business Intelligence, Centralised Data Management, Strategic Business Analysis, and professional standards for Business Analysis. Learners will gain an understanding of Data Types and Formats, Data Collection, and management strategies, including functional business data sources and assessment techniques.
The content supports learners in developing enhanced knowledge and critical appraisal skills for Statistical and Machine Learning Driven Analytics, encompassing Descriptive, Predictive, and Prescriptive Analytics. Learners will utilise this knowledge to scaffold their strategic and critical thinking in Decision Making, Data Modelling, Exploratory Data Analysis, and visualisation for managerial purposes.
Learner will be enabled to construct their strategic and critical understanding of appropriate methods for Decision Making and Data Modelling, Exploratory Data Analysis and visualisation for Managers. Furthermore, learners will acquire skills to navigate emerging Disruptive Technologies for business, employing a 3E (Empirical, Experiential, and Evidence) framework to incorporate concepts such as Big Data Technologies, the cloud with its evolving capabilities as opportunities, Sustainable technological and digital practices for managers and organisation, and AI-Enabled Analytics into business intelligence and decision-making processes.
The module also provides opportunities for learners to scaffold existing knowledge with Organisational and Behavioural biases impacting decision-making, Strategic Business Analytics in evolving Business functions, Business Data Governance, operational and process methodology, and Ethical considerations (reasoning and code) for Data and Business Analytics practices.
Learning and Teaching Methods
| Activity Type | Hours |
|---|---|
| Lecture | 10 |
| Practical Classes and Workshops | 30 |
| Independent Study | 100 |
| Directed Study (Including online independent learning) | 10 |
| Formative assessment - independent | 10 |
| Active/Simulation based | 10 |
| Groupwork | 10 |
| Interdisciplinary Work | 10 |
| Problem/Challenge based learning | 10 |
| Total Hours Selected | 200 |
Learning Outcomes
| # | Learning Outcome |
|---|---|
| LO1 | Determine and use analytical techniques to assess practical situations and interpret real-world complex data. |
| LO2 | To critically apply state-of-the art business concepts to make data-driven decisions. |
Module Requisites
N/A
Assessment Criteria
| Assessment Category | Assessment Type | Description | Duration | Word Count | Weight (%) | Best of? | Pass Mark |
|---|---|---|---|---|---|---|---|
| Asynchronous Assessment | Practical Coursework (Asynchronous) | Practical application of business analytics concepts within decision-making contexts. Through tasks emphasising data manipulation, analysis, and visualisation for business intelligence and decision making | 0 | 2000 | 50 | No | 40 |
| Asynchronous Assessment | Report 1 | Write up to produce a comprehensive report on the practical coursework undertaken throughout the module. This report should delve into various aspects of the practical work, focusing particularly on sustainable practices, disruptive technology, and the ethical implications of artificial intelligence and intelligence ethics relevant to the practical tasks completed | 0 | 2000 | 50 | No | 40 |
Assessment Matrix
| Assessment Type | Learning Outcomes | ||
|---|---|---|---|
| LO1 | LO2 | ||
| Practical Coursework (Asynchronous) | ✔ | ✔ | |
| Report 1 | ✔ | ✔ | |