Introduction to Data Analytics with Microsoft Excel

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 Analytics? What’s Changed?
  • How to 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 our data
  • How to Present You data and bring the story together
Description:

Requirements

  • 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 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
  • 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

  • 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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