module specification

This module focusses on the methods and techniques of using Big Data in business with a specific focus on organisations operating within the built environment. Given the increase in available Big Data, organisations are aware of the need to effectively utilise Big Data to gain competitive advantage. In this module, you will explore means by which organisations can benefit from Big Data.

You will appraise the technologies available to organisations and means to deploy them to aid the decision-making process.  Using data analytics and data visualisation tools you will prepare and present solutions to scenario-based problems.

By the end of the module, you should be able to demonstrate a deep knowledge and understanding of:

• The business opportunity and value creation possible through the utilisation of Big Data and business analytics
• How to appraise and select appropriate approaches to Big Data technologies and business analytics
• How to achieve business advantage through the analysis of Big Data
• Means to present Big Data to a variety of audiences using visualisation tools

The syllabus is informed by contemporary research and practice in the area of Big Data Analytics. Topics will include:

• Introduction to the age of big data (LO1)
• Big data and competitive business advantages (LO1,2)
• Big data strategies (LO2)
• Big data - Methods, techniques, and tools (LO2,3,4)
• Big data and the project lifecycle (LO2,5)
• Visualisation tools (LO4)
• Ethics and big data capture, analysis, and use (LO2,5)
• Future developments in big data capture, analysis, and use (LO1,2)

A blended/ technology enhanced learning approach will be employed in the delivery of this module. Student teaching and learning will consist of weekly classes comprising a combination of lectures, seminars, discursive sessions, and workshops. Formal lectures will introduce and develop themes that relate to the core subject. Workshops will facilitate group study of authentic datasets, presenting typical problem-based learning challenges which will require the students to propose and test solutions and evaluate the outcomes. Students will be given the opportunity to engage in seminar activities which help them to develop a deep understanding of the management of big data in the context of the built environment. Tasks will be performed through group and independent study, to develop critical thinking skills of analysis, evaluation, and synthesis. Where appropriate, activities will be captured and made available to allow asynchronous access.

Problem based learning encourages independent learning through proposing a problem which is complex with more than one right answer, challenging the students to work individually and in small groups to develop solutions, thereby developing their problem-solving abilities.  Staff will act as facilitators throughout the activities.

Throughout the module student output’s will be reviewed, and formative feedback will be given to ensure clarity and comprehension.

The learning and teaching in classes will be supported by the University’s VLE and a blended learning approach, sharing class materials, recommended reading, and case studies. Group tutorials will also be offered to support students in the preparation of their assessments, with opportunities for students to receive forward feedback.

You will reflect on your learning which will contribute towards your online Professional Development Journal (PDJ).

On completion of the module the learner, operating independently and applying their knowledge and skills, should be able to:

1. Propose how the utilisation of big data can create opportunity for businesses.
2. Appraise big data technologies and data analytics in the context of the built environment.
3. Analyse big data and make decisions to achieve positive outcomes.
4. Generate and present solutions using a data visualisation tools.
5. Communicate solutions at different levels of details to a client and project team audience.

The module coursework integrates the key issues raised in the module including the real-world context of data capture, analysis, and use. They will require the student to demonstrate deep knowledge and understanding of how data can be used to inform a decision making in line with client organisation’s strategy. 

Coursework 1:  Individual project (1450 words) 50%

Coursework 1 is an individual submission and requires the student to source and analyse a data set relevant to a real-world problem in the built environment.  Further detail will be provided in the coursework briefing document

Coursework 2:  Individual presentation (15 mins plus Q&A) 50%

Coursework 2 takes the data set from coursework 1 and requires the student to use data visualisation tools to present their findings and support their decision making.

Assessment choice is provided to the students who can agree with the module team the format of the presentation which, for example, could be live in person, a recorded talking head video, or a recorded PowerPoint presentation with commentary.
If recorded, then there will still be a scheduled opportunity for Q&A. Further detail will be provided in the coursework briefing document.

There is no single text currently in publication that provides a comprehensive coverage of all aspects of this module. There are several books which cover various parts of the module in some detail, and these are listed in the core text list.

Core:-

Data Strategy: How to Profit from a World of Big Data, Analytics and Artificial Intelligence by Bernard Marr  | 3 Oct 2021

Big Data Demystified: How to use big data, data science and AI to make better business decisions and gain competitive advantage by David Stephenson  | 12 Feb 2018

Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results Hardcover – 12 April 2016 by Bernard Marr  (Author)