1. Understand and appraise the contribution of data to the business environment and the impact on decision making.
Knowledge and Understanding
Analysis

2. Identify and analyse data from a range of business operations, highlighting positive, neutral and negative performance.
Enquiry
Analysis

3. Recommend appropriate future organisational developments based on performance highlighted in business data.
Application
Problem Solving
Learning

1. Initial Assessment, MCQ (0.5hr) (15%) (LO1)
2. Group poster presentation, comprising of a visual data dashboard with recommendations on appropriate future organisational developments, informed by performance and ethical decision making (digital poster) (10 mins) (25%) (LO3)
3. Individual Report, exploring the role and contribution of data in the business environment. Using a selected business, analyse performance data and present positive, neutral and negative performance indicators. (1,500 words) (60%) (LO2)

This module will introduce you to data from a range of business operations including marketing, finance and human resource management and how understanding and analysis can encourage improved organisational performance. Assessing and analysing data will be core to this module, focusing on how to recognise positive, neutral and negative organisational performance. Transferrable skills in ethical decision making, communication and management will also be developed.

This module will support your knowledge development on the importance of understanding business performance to drive sustainability, innovation and growth.

Data is the currency of the 21st century. In this module, you will explore the increasingly pervasive role of data in society, and how organisations can capture and leverage data to better understand consumer preferences, tailor communication, anticipate changes in external environments and manage risk and uncertainty.

Learning and teaching activities will include face-to-face which will include groupwork, formal teaching, case study analysis and students will be encouraged to share their workplace experiences with others. Online live webinars to take the form of tutorials involving opportunities for group discussion and presentation, flipped-classroom opportunities, further groupwork and case study analysis.

To support skills in data analysis, students will be encouraged to complete the Microsoft Office Specialist (MOS) Excel Examination.

You will undertake ‘formative’ assessments during the module to help you monitor your learning and provide you and us with ongoing feedback on your progress, that helps you prepare for the ‘summative assessment(s) during or at the end of the module.

These are indicative only. You will be expected to complete independent extended reading.

Maheshwari, A. (2019), Big Data Made Accessible: 2019 edition Kindle Edition
Cox, I. (2016) Visual Six Sigma: Making Data Analysis Lean 2nd Edition John Wiley and Sons
Du, H., (2013) Data Mining Techniques and Applications: an introduction Cengage
Marr, B. (2016 ) Big Data in practice : how 45 successful companies used Big Data analytics to deliver extraordinary results Wiley
Lans, Rick F. van der 2012, Data virtualization for business intelligence systems: revolutionizing data integration for data warehouses, Morgan Kaufmann, San Francisco, Calif;Oxford
Schmarzo, B. & Books24x7, I. 2013, Big data: understanding how data powers big business, 1st edn, John Wiley & Sons, Indianapolis, IN.
Whigham, D. 2007, Business data analysis using Excel, Oxford University Press, Oxford.
Sorescu, A. 2017, "Data-Driven Business Model Innovation", The Journal of product innovation management, vol. 34, no. 5, pp. 691-696.
Data Protection Act 2018 and GDPR 2018

VLE learning support material to be provided for independent / self-directed learning
Linkedin Learning
Microsoft Educator Centre
Module handbook
Open Textbook Library
Microsoft Office Specialist (MOS)

N/A