Data Analytics


Making sense of new data is vital to allow organisations to carry out business, respond to changes, and take advantage of new opportunities. In this module, you will study data quality and learn how to apply data quality measures to real-life data sets. This course forms the first of a block of four that provides a hands-on introduction to gaining the skills to practise professional data analysis strategies and techniques that can be applied in a multitude of different environments. 


Course Overview

Week 1

  • Overview – sources of data, traditional/structured vs. non-traditional/unstructured

Week 2

  • Consequences of poor data quality
  • Decision-making processes within organisations

Week 3

  • Using data to support decisions and discussion of outliers
  • Data cleansing, formatting and filtering techniques

Week 4

  • Data cleansing, Extract-Transform-Load / Extract-Load-Transform processes, mapped to CrispDM 

Week 5

  • Introduction to WEKA
  • Association Rule Mining using Apriori in WEKA

Week 6

  • Clustering using WEKA to underpin theory 

Week 7

  • Exploring issues with big data 

Week 8

  • Data visualisation
  • Basic excel charts to aid visualisation

Week 9

  • Discussion on cloud data analytics 

Week 10

  • Dashboards, design issues 


Course aims

Data Analysis is only as good as the data sources and understanding of the tools and techniques needed to maximise the use of existing company data.

Part of this course will examine what data is, how to process data into information and hopefully leave the organisation with knowledge and wisdom.



Many organisations have vast databases/data sets with a limited understanding of what to do with the data, so this course will highlight how to improve the quality of data and what type of decisions could be made with basic company data. With better data and the correct tools, better decisions could be made.

The learner will be exposed to data in all its forms and the processes to ensure that data is fit for its purpose. They will also be exposed to tools that could aid with decision making, along with issues with respect to big data and cloud data analytics.



After completing this course, you will receive 20 free credits which can then be used for future learning.



The Staffordshire E-Skills & Entrepreneurship Gateway (SEGway) is part funded by the European Social Fund.

Delivery method
Blended learning

This is a 10-week course with one 2-hour session per week. 

Start date

Tuesday 26 July, 2pm-4pm 

School of Digital, Technologies and Arts

Entry requirements

This training course is exclusively available to Stoke-on-Trent and Staffordshire based students, graduates and businesses with a maximum of 250 employees.


This course is free to all Staffordshire based SMEs, students, graduates and start-up businesses. 



We have Libraries and service desks at both sites in Stoke-on-Trent and Stafford. Our experienced and friendly staff can answer your IT queries, help you to access resources, show you how to research for your assignments and help with referencing.

How to apply

To apply for this course, please email

Top 15 for Teaching Quality

The Times and The Sunday Times Good University Guide 2021

6th for Social Inclusion

The Times and The Sunday Times Good University Guide 2022

Midlands University of the Year

Midlands Business Awards 2020