Introduction to Data Analytics with Microsoft Excel

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What you’ll learn:

• What is Data Analytics & Why is it so Important
• Why Do We Need Analytics? What’s Changed?
• How to Find Appropriate Datasets to work with
• How to Analyse you Data
• The importance of Mean, Mode, Median and Range of Data
• What is the difference between Normal and Non Normal Data
• How to create a histogram
• How to find and remove outliers
• Understand what is a standard deviation and relative standard deviation
• Understand the Difference Between a Run and a Control Chart?
• The basics of working with pivot tables
• Starting to Tell Our Analytical Story
• How to Visualize our data
• How to Present You data and bring the story together

Description:

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?

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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

Who this course is for:

• Complete Beginners

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