Presentation Business management

Learning Data Analytics


Every person who works with data has to perform analytics at some point. This popular
training course—dramatically expanded and enhanced for 2018—teaches analysts and
non-analysts alike the basics of data analytics and reporting.
Robin Hunt defines what data analytics is and what data analysts do.
She then shows how to identify your data set—including the data you don't have—and
interpret and summarize data.
She also shows how to perform specialized tasks such as creating workflow diagrams,
cleaning data, and joining data sets for reporting.
Coverage continues with best practices for data analytics projects, such as verifying data
and conducting effective meetings, and common mistakes to avoid.
Then learn techniques for repurposing, charting, and pivoting data.
Plus, get helpful productivity-enhancing shortcuts and troubleshooting tips for the most
popular data analytics program, Microsoft Excel.


Learning objectives
 Define data analysis and data analyst.
 List roles in data analysis.
 Explain data fields and types.
 Define syntax.
 Explain how to interpret existing data.
 Describe data best practices.
 Repurpose data.
 Create a data dictionary.
 Compare and contrast linking versus embedding charts and data.
 Build pivot charts with slicers.



Introduction

Welcome
As we've gained control over the storage and management of data, the need has grown
for more analysts to gather and analyze information.
Data analysis is crucial in all industries. As we produce more data every year, the need for
data analysts will continue to grow.




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, Hi, I'm Robin Hunt. This course is the first step to determine where you may be on your path
to analysis and data science. You may discover you're already an analyst. We'll start by
learning about data analysts, the roles, and skills, and truth about data.
You'll learn to identify data, learn to deal with data you don't have, learn how to work with
source data, and the impacts of business roles to your data.
You'll learn to join data and build reports. You'll learn productivity enhancing shortcuts for
the data tools you may work with already. Let's get started.


What you should know

There are no prerequisites to this course other than an interest in data analysis, however,
to get the most of it, some familiarity with Excel will be helpful. We'll be using Excel and
Access throughout the course.


How to use the exercise files


To follow along with this course, you can download the exercise files to the desktop, like
I've done here. The files are organized by folder. And within each chapter folder, you'll find
the files you need for each video.
Throughout the course, we'll use one database. However, if you jump in after chapter five, I
have a finished copy of the database in the video folder for any minor modifications you
may have missed.



1. Getting Started with Data Analysis

1.1 Defining data analysis and data analyst


- [Instructor] As you will soon discover, there's a growing need for data analysis and data
analysts. So what is data analysis? There are lots of definitions but ultimately, it's the process
of inspecting, cleaning, transforming and modeling data for business decision-making.
You might then ask the obvious, what's a data analyst and let me assure you, it's not one
size fits all. Data analysts work with any one of those processes or all of them.
I'm constantly working with my team showing them the results of those processes or just
setting up data for the decision-making that needs to happen on a project by project
basis.
Data analysts' work is as diverse as the job descriptions you'll read while looking for data
jobs. The data analysts will work with data in all shapes and fashion and the tools are as
diverse as the data we encounter.




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