Introduction to Data Analytics with Microsoft Excel


Introduction to Data Analytics with Microsoft Excel, Master data analysis through Excel with advanced hands on practical training.


  • Microsoft Office 365 or Excel 2010 – 2019
  • Mac users Pivot Visuals may look slightly different to the examples shown
  • Basic experience with Excel functionality is a bonus but not required


Welcome to the world of Data Analytics, voted the sexiest job of the 21st Century.

In this expertly crafted course, we will cover a complete introduction to data analytics using Microsoft Excel, you will cover the concepts, the value and practically apply core analytical skills to turn data into insight and present as a story.

Look at this as the first step in becoming a fully-fledged Data Scientist

Course Outline

The course covers each of the following topics in detail, with datasets, templates and 17 practical activities to walk through step by step:

What is Data Analytics

  • Why Do We Need It in this new world
  • Thinking about Data, how it works in the lad v how it works in the wild
  • Qualitative v Quantitative data and their importance

Finding Your Data

  • How to find Sources of Data and what they contain
  • Reviewing the Dataset and getting hands on

Analysing Your Data

  • Mean, Modes, Median and Range
  • Normal and Non normal Data and its impacts to predictability
  • What is an Outlier in our data and how do we remove
  • Distribution and Histograms and why they are important
  • Standard Deviation and Relative Standard Deviation, why variance is the enemy
  • What are Run and Control charts and what do they tell us?

Working With Pivot Tables

  • How the Pivot Builder Works
  • Setting Our Headers
  • Working with calculated fields
  • Sorting and Filtering
  • Transforming Data with Pivot Tables

Data Engineering

  • How to create new, insightful datasets
  • The importance of balanced data
  • Looking at Quality, Cost and Delivery together

Start Telling Our Analytical Story

  • What is your data telling?
  • Ask Yourself Questions
  • Transforming Data into Information

Visualizing Your Data

  • Levels of Reporting
  • What Chart to Use
  • Does Color Matter
  • Let’s Visualize Some Data

Presenting Your Data

  • Bringing The Story Together with a Narrative

Practical Activities

We will cover the following practical activities in detail through this course:

  • Practical Example 1 – Mean, Mode, Median, Range & Normality
  • Practical Example 2 – Distribution and Histograms
  • Practical Example 3 – Standard Deviation and Relative Standard Deviation
  • Practical Example 4 – A Little Data Engineering
  • Practical Example 5 – Creating a Run Chart
  • Practical Example 6 – Create a Control Chart
  • Practical Example 7 – Create a Summary Pivot of Our Claims Data
  • Practical Example 8 – Transforming Data
  • Practical Example 9 – Calculated Fields, Sorting and Filtering
  • Practical Example 10 – Lets Engineer Some QCD Data
  • Practical Example 11 – Lets Answer Our Analytical Questions with Pivots
  • Practical Example 12 – Visualizing Our Data
  • Practical Example 13 – Lets Pull our Strategic Level Analysis Together
  • Practical Example 14 – Lets Pull our Tactical Level Analysis Together
  • Practical Example 15 – Lets Pull our Operational Level Analysis Together
  • Practical Example 16 – Lets Add Our Key Findings
  • Practical Example 17 – Lets Add Our Recommendations

Who this course is for:

  • Anyone who works with Excel on a regular basis and wants to supercharge their skills
  • Excel users who have basic skills but would like to become more proficient in data exploration and analysis
  • Students looking for a comprehensive, engaging, and highly interactive approach to training
  • Anyone looking to pursue a career in data analysis or business intelligence

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