This module provides the skills and concepts necessary to solve problems in Business Intelligence. Topics addressed include the following and represent the state of the art in Business Intelligence:



The nature of Knowledge Discovery, and the role and contribution of Machine Learning, Data Mining, Organisational Decision Making and Data Science.
Data Quality and ethics in machine learning and Big Data Analytics
The nature of Big Data and Big Data Analytics and the selection of analysis strategies
Professional issues and obligations in relation to data analysis

Legal aspects of data including data Privacy and governance

Data Visualisation for decision making

Visualisation and communication of the results of analysis

Use of IoT for acquiring accurate and timely data

Use of dashboards and command and control applications for managing data / data feeds

Student report - Students will work on an investigative solution to a Business Intelligence problem (from a given case study) and create an analytical report on their findings (Learning Outcomes 1 to 3).

Students will have participated in an award induction workshop where they will learn how to use the Virtual Learning Environment (VLE) employed for the study of this module. Subsequently students will work through the module material provided on the VLE at a pace suggested within the VLE for the module. The material will include activities that allow students to assimilate the concepts and skills required by the module. Students will be encouraged to discuss relevant aspects via vehicles such as discussion forums hosted within the VLE. The forums will allow discussion with a student's peer group as well as the module tutor. Teleconferencing meetings will occur as appropriate to provide additional support.

1. Plan and develop business reporting systems using state of the art visualization and dashboard technologies

Communication, Knowledge and Understanding, Application



2. Query, analyse and develop business data using data mining techniques and web analytics

Analysis, Application



3. Evaluate major principles and techniques of data management and discovery using different applications, processes and technologies

Application, Reflection

Harper, J. (2019) Data Science For Business: How To Use Data Analytics and Data Mining in Business, Big Data For Business, Springer

Du, H., (2013) Data Mining Techniques and Applications: an introduction Cengage

Atluri, D, (2022), SAP Data Intelligence: The Comprehensive Guide, SAP Press

Clarke, E, (2022), Everything Data Analytics-A Beginner's Guide to Data Literacy: Understanding the Processes That Turn Data Into Insights (All Things Data), Kenneth Michael Fornari¿Publishing



Advanced/Supplementary Text/Resource:

Use of library resources such as LinkedIn videos

General data analytics software

A standard PC

Data is key to business intelligence and this module focuses on how organisations can manage their infrastructure to support timely and strategic decisions through acquiring, analysis and using data backed solutions. The module will introduce practical aspects and get students to think through problems and document solutions to these.