Unit 12: Data Analytics


Unit code                            K/615/1637

Unit level                            QCF Level 4/ NFQ Level 6

Credit value                       15


Introduction

Like the physical universe, the digital universe is enormous and is doubling in size every two years. By 2020 the digital universe – the data we create and copy annually – is projected to reach 44 zettabytes or 44 trillion gigabytes.

Data is  everywhere in the world. Without knowing  how to interpret this data it would be difficult to understand its meaning or make use of the data to increase the productivity of an organisation. Data analytics is a range of processes that converts data into actionable insight  using a range of statistical techniques. Data analytics is a relatively new term – it is an overarching term for all decision support and problem-solving  techniques. Most of the time the term ‘data analytics’ and ‘business analytics’ are used interchangeably.

This unit will introduce the theoretical foundation of data analytics and a range of data analytic processes and techniques to provide hands-on experience for enhancing students’ skills.

Topics included in this unit are: data analytic terminologies, types of data analytics, data exploration and visualisation, understanding  data with descriptive, predictive and prescriptive analytics.

On successful completion of this unit students will be able to understand the theoretical foundation of data analytics, data analytic processes and techniques.

Moreover they will gain hands-on experience of implementing  data analytic processes and techniques using a programming language such as Python, R, or a tool such as Weka, KNIME, PowerBI, Exc el etc.

As a result students will develop skills such as communication literacy, critical thinking, analysis, reasoning and interpretation which are crucial for gaining employment and developing academic competence.

 

Learning  Outcomes

By  the end of this unit students will be able to:

LO1      Discuss the theoretical foundation of data analytics that determine decision- making  processes in management  or business environments.

LO2      Apply a range of desc riptive analytic techniques to convert data into actionable insight  using a range of statistical techniques.

LO3      Investigate a range of predictive analytic techniques to discover new knowledge for forecasting future events.

LO4      Demonstrate  prescriptive analytic methods for finding the best course of action for a situation.