Business Analytics Programming

Module overview

This course provides part of the essential knowledge and skills required for conducting the Final Project module in the final year. It introduces the fundamentals of data analytics programming using appropriate software tools. Upon successful completion, you will be able to read, access, manage and manipulate large datasets; solve data-driven problems; save programs and datasets; apply conditional logic; combine multiple data sources; and produce tables and data listings. You will also gain experience with core data analysis technique.

Linked modules

Pre-Requisites: MANG1019 or MANG1047

Aims and Objectives

Learning Outcomes

Transferable and Generic Skills

Having successfully completed this module you will be able to:

use your analytic skills in problem solving;
communicate technical ideas to non-specialist managers.

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

store data using appropriate data management structures within such tools.
read structured and unstructured data stored in popular formats such as excel worksheets, text tables into data analytics programming tools;

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

key computer programming concepts for managing and analysing ‘big data';
the fundamental features of data analytic programming tools and how they are used to manage, analyse and report data;
how to manipulate, analyse, visualise and report data using data analytics programming tools.

Learning and Teaching

Teaching and learning methods

Teaching methods include: • Lectures • Interactive case studies • Computer labs • Directed reading • Private/guided study Learning activities include: • Introductory lectures • 2 assignments (individual written coursework) • Case study • In class debate and discussion • Private study • Use of video and online materials

Study time
Type	Hours
Teaching	36
Independent Study	114
Total study time	150

Resources & Reading list

Textbooks

Peng, J.C.Y (2009). Data Analysis Using SAS. Sage.

Lutz, M. (2025). Learning Python: powerful object-oriented programming. 6th Edition. O’Reilly Media, Inc..

Assessment

Formative

This is how we’ll give you feedback as you are learning. It is not a formal test or exam.

Class participation

Assessment Type: Formative
Feedback:
Final Assessment: No
Group Work: No

Summative

This is how we’ll formally assess what you have learned in this module.

Breakdown
Method	Percentage contribution
Program	20%
Data analysis project	80%

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Breakdown
Method	Percentage contribution
Data analysis project	100%

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.

Breakdown
Method	Percentage contribution
Data analysis project	100%

Repeat Information

Repeat type: Internal & External