From Everyday Data Visualization by Desireé Abbott

Everyday Data Visualization is a field guide for design techniques that will improve the charts, reports, and data dashboards you build every day. The foundation of data visualization is storytelling, and this book gives you the tools you need to start telling those stories with clarity, precision, and flair!


Analysts don’t just write code or wrangle Excel anymore – the lines are blurring between analyst, designer, and developer. Data visualization is already busting out of the spreadsheet and into the app, the game, the heads-up display on your car. We are surrounded every day by data and numbers – about how we spend our time, how much we sleep, how healthy we are (or aren’t), how bad is the traffic, how we’ve scored in the games we play, how much money we’ve saved, how much money we’ve spent, etc.

Of course the deluge of data doesn’t stop with our personal lives but carries into the workplace as well. First responder agencies need to know to how many calls for service they have responded in a given timeframe and where those calls were. Farmers want to know what crops have been planted in which fields for how many seasons, and where the yield was the greatest. Utility companies want to know the peak times for demand of their service. Tech companies want to know who’s subscribing to their product, which ads led to the most purchases, how long are customers maintaining their subscriptions, and how much profit each customer generates in their lifetime. Retailers want to know which products sell the best to which demographics. As such, the demand for the skills to communicate with data grows daily.

In this book, the reader will learn to hone their data communication skills. You’ll learn not just about how to choose a good chart type for their data, but how to lay out their entire visualization to best get their point across. You’ll learn where to place various elements to maximize impact, and they’ll learn about how to use color and typography to set the tone of their work and keep their reader’s attention.

Oftentimes when analysts build dashboards and reports, they throw some charts on a page and call it done. I’m here to argue for finesse, design rigor, and great attention to detail. You will learn to build easy-to-consume, delightful-to-use dashboards and reports that offer meaning and insight into data which users will want to return to again and again.

Designing for data that changes is different than designing a static report. In this book, you will be empowered to design flexible visualizations that will breathe and grow and automatically update as their underlying data changes and expands.

With changing data comes changing reports. You will learn to design for not only the “happy path” – the lovely time when everything fits perfectly on the page and all categories are fully and nicely populated – but they will also learn to account for the opposite, the “sad path” – the times when there are missing dates in the time series, or early on in data collection when categories are only just emerging and are barely populated yet.

You will learn to effectively use color to convey meaning, and typography as a way to communicate a hierarchy of importance of information. Both color and typography together also alter the tone of a visualization – at times more subtly than others – so you will also learn to harness these tools to set the correct first impression when a user encounters a visualization.

Who is this book for?

This book is for people who work in the following sorts of jobs:

  • Business analyst
  • Data analyst
  • BI Developer
  • Data scientist
  • Any other job where you need to compellingly display data

And work with the following types of mediums to display data:

  • Slides
  • Charts and graphs
  • Website graphics
  • Internal sites
  • Dashboards
  • Business reports

And use the following sorts of tools:

  • Excel
  • PowerPoint
  • R/Python
  • Tableau
  • PowerBI

The minimally qualified reader of this book should have the following skills:

  • Some exposure and access to data that needs to be presented to users is recommended.
  • Also, it would be helpful to have some kind of visualization project ready, but isn’t really necessary.

Other skills that could be helpful are:

  • Experience with constructing calculations and charts in Excel or other spreadsheet programs
  • Experience with a BI tool such as Tableau, Qlik, or Power BI
  • ccess to some sort of database, data lake, or data warehouse, e.g. Amazon Redshift, MySQL, Postgres, Teradata, Snowflake, etc. AND the ability to write SQL queries against said database, data lake, or data warehouse
  • Access to some sort of data or streaming API AND the ability to wrangle the output of said API, shaping it for your own purposes
  • Access to “flat” text files, such as CSV (comma-separated values) or TSV (tab-separated values), which store data in columns
  • Access to “flat” JSON files which store data in a nested, key-value pair structure (this wouldn’t work well with spreadsheet programs)

What will you learn from this book?

In short, you’ll learn to make compelling data visualizations and have lots of fun doing it!

Here is a non-exhaustive list of what you can expect to learn from this book:

  • How to harness the power of perception to guide a user’s attention
  • How to effectively use color and other design fundamentals to bring data to life
  • How to choose the optimal chart type for the data and the story you want to tell
  • How to best design for interactive visualizations, rather than static ones
  • How to approach a visualization project from end-to-end, keeping the user’s needs first throughout the journey

If you want to learn more, check out the book here.