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.
Requirements
- 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
Description
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
