MQM2DAS: Data Analytics Strategy in Business
Module code: MQM2DAS
Module provider: Business Informatics, Systems and Accounting; Henley Business School
Credits: 20
Level: 7
When you'll be taught: Full year
Module convenor: Professor Keiichi Nakata, email: k.nakata@henley.ac.uk
Pre-requisite module(s):
Co-requisite module(s):
Pre-requisite or Co-requisite module(s):
Module(s) excluded:
Placement information: No placement specified
Academic year: 2024/5
Available to visiting students: No
Talis reading list:
Last updated: 19 November 2024
Overview
Module aims and purpose
The aim of this module is to evaluate the business value in utilising data analytics and develop information and data management solutions with an appreciation of data analytics methods and technologies. It also develops understanding of the legal, social and ethical concerns involved in data management and analysis.
This module focusses on the strategic use of data analytics in business in the era of Big Data. Given the availability of large amounts of data in business and organisation, there is an increasing need for organisations to assess how effectively data analytics and relevant emerging technologies can be utilised for business. In this module, students consider how organisations can benefit from Big Data and analytics and analyse business and technological requirements to create value though these technologies. Students will also explore recent developments in technologies surrounding Big Data and data analytics such as text analytics, visual analytics and artificial intelligence, and assess types of tools that can be utilised, including the evaluation and use of state-of-the-art tools. Students will also assess the legal and ethical implications of data analytics in business.
Module learning outcomes
By the end of the module, it is expected that students will be able to:
1. Assess the business opportunity and value creation through the utilisation of business data analytics by analysing the business environment and requirements;
2. Critically assess suitable data analytics technologies and business analytics approaches;
3. Formulate a solution for achieving value through data analytics;
4. Scope and deliver data analysis projects, in response to business priorities, create compelling business opportunities reports on outcomes suitable for a variety of stakeholders including senior clients and management;
5. Demonstrate the awareness and understanding of the information governance requirements that exist in the UK, and the relevant organisational and legislative data protection and data security standards that exist.
6. Assess and address the organisational and technical impact of implementing the solution, including the legal, social and ethical concerns involved in data management and analysis
Module content
• Introduction; Business opportunity of data analytics in the era of big data
• Big data and data analytics strategy
• Business analysis for data analytics and business intelligence
• Methods, techniques and tools for big data and analytics
• Developing a data analytics strategy
• Big Data visualisation
• Strategic use of artificial intelligence and machine learning technologies
• Professional, leadership, social, legal and ethical issues in implementing data analytics solutions
• Emerging issues and impacts of big data analytics
Structure
Teaching and learning methods
This module combines lectures, seminars and practical workshops to develop data analytics strategies. It also explored the uses of state-of-the-art analytics tools as part of developing a data analytics solution in business as a project.
In completing the coursework assignment, students will be expected to produce a data analytics strategy for a particular business context, based on which an individual report is produced. The assignment will provide students an opportunity to communicate critically and concisely their findings which demonstrate their extended understanding of the subject.
The contact hours are shown for one semester in the table below for illustrative purposes only. The actual timing will vary depending on your cohort start date.
A two-day workshop will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online.
Study hours
| Scheduled teaching and learning activities | Semester 1 | Semester 2 | Summer |
|---|---|---|---|
| Lectures | 14 | ||
| Seminars | |||
| Tutorials | |||
| Project Supervision | |||
| Demonstrations | |||
| Practical classes and workshops | |||
| Supervised time in studio / workshop | |||
| Scheduled revision sessions | |||
| Feedback meetings with staff | |||
| Fieldwork | |||
| External visits | |||
| Work-based learning | 24 | ||
| Self-scheduled teaching and learning activities | Semester 1 | Semester 2 | Summer |
|---|---|---|---|
| Directed viewing of video materials/screencasts | 10 | ||
| Participation in discussion boards/other discussions | 10 | ||
| Feedback meetings with staff | |||
| Other | |||
| Other (details) | |||
| Placement and study abroad | Semester 1 | Semester 2 | Summer |
|---|---|---|---|
| Placement | |||
| Study abroad | |||
| Independent study hours | Semester 1 | Semester 2 | Summer |
|---|---|---|---|
| Independent study hours | 142 |
Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.
Semester 1 The hours in this column may include hours during the Christmas holiday period.
Semester 2 The hours in this column may include hours during the Easter holiday period.
Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.
Assessment
Requirements for a pass
Students need to achieve an overall module mark of 50% to pass this module.
Summative assessment
| Type of assessment | Detail of assessment | % contribution towards module mark | Size of assessment | Submission date | Additional information |
|---|---|---|---|---|---|
| Written coursework assignment | Report | 100 | 20 pages of A4 | Submission deadlines are provided in your cohort schedule and can be found on Canvas |
Penalties for late submission of summative assessment
This module is subject to the Penalties for late submission for Postgraduate Flexible programmes policy, which can be found at:
The Module Convenor will apply the following penalties to work submitted late:
- where the piece of work is submitted up to one calendar month after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark;
- where the piece of work is submitted more than one calendar month after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.
Formative assessment
Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.
Reassessment
| Type of reassessment | Detail of reassessment | % contribution towards module mark | Size of reassessment | Submission date | Additional information |
|---|---|---|---|---|---|
| Written coursework assignment | Report | 100 | 20 pages of A4 | Submission deadlines are provided in your cohort schedule and can be found on Canvas |
Additional costs
| Item | Additional information | Cost |
|---|---|---|
| Computers and devices with a particular specification | ||
| Printing and binding | ||
| Required textbooks | ||
| Specialist clothing, footwear, or headgear | ||
| Specialist equipment or materials | ||
| Travel, accommodation, and subsistence |
THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.