Analytics have become one of the most powerful tools available to decision makers. The module is designed to introduce students to a variety of predictive techniques using industry-standard (but highly accessible) purpose-designed software, geared to the special nature of ‘Big Data’. The purpose of the module is to develop student’s skills in the use of data and models to support decision making in business.
The module also exposes students to emerging technologies and their application to business.
Introduction to Data Analytics
Understanding data analytics; customer centric data analytics; the business case for data analytics; understanding how data analytics can solve business problems; pitfalls to avoid.
Data Analytics Life Cycle
The stages of a data analytics project; examples of lifecycle models; CRISP DM.
Data Preparation
Understanding data; data quality; data preparation.
Exploratory Data Analysis
Descriptive analysis of individual variables & relationships between variables
Predictive Data Analysis
Regression analysis, Classification analysis.
Business Decision Making
The types of decision data analysis can support; using data analysis to make business decisions; data analysis in practice. Visualising and communicating findings.
Emerging Technologies
In conjunction with ConnectED Tech Seminar Series. Emerging technologies, digital transformation, AR/VR, Block-chain, AI, 5G, Internet of Things.
The module will incorporate a range of teaching and learning methods including lectures, class discussion, computer lab work and seminars. The learning environment will be practical, integrative with a hands-on approach on using software to analyse and model data to find solutions to real-world problems.
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Other Assessment(s) | 100 |