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 acquiring the skills to practice 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, storage paradigms
  • DAMA definitions of data quality, the Data Quality Lifecycle

Week 2

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

Week 3

  • Using data to support decisions
  • Data cleansing, formatting and filtering techniques in Microsoft Excel

Week 4

  • Data cleansing, Extract-Transform-Load / Extract-Load-Transform processes in SQL Server Integration Services
  • The scientific method; formulating and testing hypotheses

Week 5

  • Reproducibility and falsifiability in scientific experiments
  • Quantitative statistical testing methodologies – Student’s t-test, and p-value calculation

Week 6

  • Introduction to WEKA
  • Linear regression using WEKA

Week 7

  • Association Rule Mining using Apriori in WEKA
  • Descriptive statistics, grouping and aggregation using Microsoft Excel

Week 8

  • Introduction to the R language, using RStudio
  • Design practices in data visualisation

Week 9

  • Data analysis and visualisation techniques in R
  • Connecting to external data sets in Excel
  • Graphs and charts in Excel; Power Query, Power View

Week 10

  • Preparing dynamic reporting for Power BI
  • Using Shiny for custom reporting visualisations


On completion of this course, learners will receive a certificate of learning and will also gain 20 credits.


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

Delivery method
Blended learning
Online learning

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

Start date

March 2022

School of Digital, Technologies and Arts

Entry requirements

This level 6 module is open to individuals who have achieved A-Levels or indviuals who are currently in a data analytics job role. 


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

How to apply

To apply for this course, please email

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