Data analytics may seem daunting, but if you're an experienced Excel user, you have a unique head start. With this hands-on guide, intermediate Excel users will gain a solid understanding of analytics and the data stack. By the time you complete this book, you'll be able to conduct exploratory data analysis and hypothesis testing using a programming language.

Exploring and testing relationships are core to analytics. By using the tools and frameworks in this book, you'll be well positioned to continue learning more advanced data analysis techniques. Author George Mount, founder and CEO of Stringfest Analytics, demonstrates key statistical concepts with spreadsheets, then pivots your existing knowledge about data manipulation into R and Python programming.

This practical book guides you through:

• Foundations of analytics in Excel: Use Excel to test relationships between variables and build compelling demonstrations of important concepts in statistics and analytics
• From Excel to R: Cleanly transfer what you've learned about working with data from Excel to R
• From Excel to Python: Learn how to pivot your Excel data chops into Python and conduct a complete data analysis

Learning Objective

By the end of this book, you should be able to conduct exploratory data analysis and hypothesis testing using a programming language. Exploring and testing relationships is core to analytics. With the tools and frameworks you’ll pick up in this book, you will be well positioned to continue learning more advanced data analysis techniques.

We’ll be using Excel, R, and Python because these are powerful tools, and because they make for a seamless learning journey. Few books cover this combination, even though the progression from spreadsheets into programming is common for analysts, myself included.

Pre-requisites

To meet these objectives, this book makes some technical and technological assumptions:

Technical requirements: I am writing this book on a Windows computer with the Office 365 version of Excel for desktop. As long as you have a paid version of Excel 2010 or greater for either Windows or Mac installed on your machine, you should be able to follow along with the majority of the instruction in this book, with some variations, particularly with PivotTables and data visualization. R and Python are both free, open source tools available for all major operating systems. I address how to install them later in the book.

Technological requirements: This book assumes no prior knowledge of R or Python; that said, it does rely on moderate knowledge of Excel to flatten that learning curve. The Excel topics you should be familiar with include the following:

• Absolute, relative, and mixed cell references
• Conditional logic and conditional aggregation (IF() statements, SUMIF()/SUMIFS(), and so forth)
• Combining data sources (VLOOKUP(), INDEX()/MATCH(), and so forth)
• Sorting, filtering, and aggregating data with PivotTables
• Basic plotting (bar charts, line charts, and so forth)

Review

"This book is uniquely poised to be used as both a reference and a primer on business and data analytics" - Aiden Johnson, Data Scientist & Mentor at BreakthroughData Science

"George lays out exactly what you need to do to bridge from Excel into data science and analytics." - Jordan Goldmeier, Microsoft Excel MVP and Head of Anarchy Data

"I benefited from this book by learning the technical progression from Excel into Python and R languages. I also took conceptual knowledge of statistics into these playgrounds." - Data Analyst at josephbalog.com

"The book was written in a way that helps readers transfer their knowledge about data into new tools and techniques in an approachable manner." - Nicole LaGuerre, Learning & Development Consultant at s1mplythebest.com

"Not only will the reader become comfortable with using the most popular data analysis programming languages, they will also learn about techniques to wrangle, explore, and visualize data so that it comes to life and tells a story." - John Dennis, Data Analytics & Data Science Consultant

"I have been looking for the most direct line to acquire the essential skills required to perform in a data analytics/data science role at an affordable price point. This book ... provides the closest thing to the roadmap that I've been looking for." - Barry Lilly, Claims Team Manager at Liberty Mutual Insurance

"This book is a gold mine for anyone who wants to levelup their analytics game. It's an excellent review of major analytical concepts and also a great starting point for learning how to munge data programmatically using R or Python." - Tobias Zwingmann, Senior Data Scientist and Co-founder of RAPYD.AI

About the Author

George Mount is the founder and CEO of Stringfest Analytics, a consulting firm specializing in analytics education and upskilling. He has worked with leading bootcamps, learning platforms and practice organizations to help individuals excel at analytics. George regularly blogs and speaks on data analysis, data education and workforce development.

George holds a bachelor’s degree in economics from Hillsdale College and master’s degrees in finance and information systems from Case Western Reserve University. He resides in Cleveland, Ohio.