Data Mining for Business module (BU51050)

Organisations generate vast amounts of data, whether it be numerical or text, but value comes from knowing how to analyse it. This module gives you the technical knowledge and practical skills to do that.

You'll start with the data mining process, from problem definition and data preparation through to model evaluation and deployment. You'll then work through the main families of methods: classification algorithms such as decision trees, clustering techniques, and association analysis for pattern discovery.

Text mining forms a dedicated part of the module, giving you tools to extract insight from unstructured data. You'll also study the principles of model evaluation and learn how to select appropriate methods for different business problems.

Throughout, you'll develop hands-on experience with analytical tools used in practice, and build your ability to communicate technical findings clearly to business audiences.

What you will learn

In this module, you will:

• Understand the data mining process and how it applies to business decision-making
• Apply classification, clustering, and association rule mining methods to real datasets
• Use text mining techniques to extract insight from unstructured data
• Evaluate and compare data mining models using appropriate metrics
• Communicate analytical findings clearly to both technical and non-technical audiences

By the end of this module, you will be able to:

• Explain the main data mining and machine learning methods and their applications in business
• Apply classification, clustering, and association rule algorithms to business datasets
• Use text mining methods to analyse unstructured data
• Evaluate the performance of data mining models and select appropriate techniques for given problems
• Communicate data mining findings clearly and accurately

Assignments / assessments

Lab Assignment (40%)

• You will be given a dataset and asked to select, apply and justify choice of data preprocessing and exploratory analysis techniques
• Given in Week 4
• Due in Week 4
• 3 hours of effort expected

Data Mining Report (60%)

• You’ll be given a data mining problem and asked to evaluate appropriate methods, apply them to data, and present your results clearly
• Given in Week 9
• Due in Week 11
• 10 hours of effort expected

This module does not have a final exam

Teaching methods / timetable

This module is taught through a combination of lectures and computer lab workshops.

In the first part of the module, you will learn how to prepare data for analysis. This includes data cleaning, data preparation, and exploratory analysis.

In the middle part of the module, you will study the core data mining methods used in business, alongside discussion of when each approach is most useful.

In the final part of the module, you will explore text data and learn how text mining techniques can be used to analyse unstructured business information.

Throughout the module, you will use analytical software in practical sessions and develop your ability to interpret and communicate results clearly.

Teaching is face to face and delivered on campus in Semester 1.