Description
Requirements
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Microsoft Office 365 or Excel 2010 – 2019
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Mac users Pivot Visuals may look slightly different to the examples shown
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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
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Why Do We Need It in this new world
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Thinking about Data, how it works in the lad v how it works in the wild
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Qualitative v Quantitative data and their importance
Finding Your Data
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How to find Sources of Data and what they contain
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Reviewing the Dataset and getting hands on
Analysing Your Data
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Mean, Modes, Median and Range
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Normal and Non normal Data and its impacts to predictability
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What is an Outlier in our data and how do we remove
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Distribution and Histograms and why they are important
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Standard Deviation and Relative Standard Deviation, why variance is the enemy
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What are Run and Control charts and what do they tell us?
Working With Pivot Tables
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How the Pivot Builder Works
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Setting Our Headers
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Working with calculated fields
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Sorting and Filtering
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Transforming Data with Pivot Tables
Data Engineering
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How to create new, insightful datasets
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The importance of balanced data
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Looking at Quality, Cost and Delivery together
Start Telling Our Analytical Story
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What is your data telling?
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Ask Yourself Questions
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Transforming Data into Information
Visualizing Your Data
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Levels of Reporting
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What Chart to Use
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Does Color Matter
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Let’s Visualize Some Data
Presenting Your Data
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Bringing The Story Together with a Narrative
Practical Activities
We will cover the following practical activities in detail through this course:
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Practical Example 1 – Mean, Mode, Median, Range & Normality
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Practical Example 2 – Distribution and Histograms
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Practical Example 3 – Standard Deviation and Relative Standard Deviation
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Practical Example 4 – A Little Data Engineering
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Practical Example 5 – Creating a Run Chart
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Practical Example 6 – Create a Control Chart
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Practical Example 7 – Create a Summary Pivot of Our Claims Data
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Practical Example 8 – Transforming Data
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Practical Example 9 – Calculated Fields, Sorting and Filtering
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Practical Example 10 – Lets Engineer Some QCD Data
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Practical Example 11 – Lets Answer Our Analytical Questions with Pivots
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Practical Example 12 – Visualizing Our Data
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Practical Example 13 – Lets Pull our Strategic Level Analysis Together
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Practical Example 14 – Lets Pull our Tactical Level Analysis Together
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Practical Example 15 – Lets Pull our Operational Level Analysis Together
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Practical Example 16 – Lets Add Our Key Findings
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Practical Example 17 – Lets Add Our Recommendations
Who this course is for:
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Anyone who works with Excel on a regular basis and wants to supercharge their skills
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Excel users who have basic skills but would like to become more proficient in data exploration and analysis
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Students looking for a comprehensive, engaging, and highly interactive approach to training
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Anyone looking to pursue a career in data analysis or business intelligence
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