Practical Tableau: 100 Tips, Tutorials, and Strategies from a Tableau Zen Master

by Ryan Sleeper

Whether you have some experience with Tableau software or are just getting started, this manual goes beyond the basics to help you build compelling, interactive data visualization applications. Author Ryan Sleeper, one of the worldâ??s most qualified Tableau consultants, complements his web posts and instructional videos with this guide to give you a firm understanding of how to use Tableau to find valuable insights in data.

Over five sections, Sleeperâ??recognized as a Tableau Zen Master, Tableau Public Visualization of the Year author, and Tableau Iron Viz Championâ??provides visualization tips, tutorials, and strategies to help you avoid the pitfalls and take your Tableau knowledge to the next level.

Practical Tableau sections

get started with Tableau from the beginningChart use step-by-step tutorials to build a variety of charts in TableauTips and learn innovative uses of parameters, color theory, how to make your Tableau workbooks run efficiently, and more explore the INSIGHT framework, a proprietary process for building Tableau dashboards learn tangible tactics for storytelling with data, including specific and actionable tips you can implement immediately

Genres: Business, Nonfiction, Computer Science, Programming, Bisexual

624 pages, Kindle Edition

Published April 3, 2018

Reviews

[William Yarberry · Rating 4 out of 5]

Well written and organized by function. I thought he could have done a better job in two areas: 1) calculated fields (e.g., COUNTD) -- needs more depth, particularly where the use of common names like TOTAL need to be discussed in depth and 2) some of issues related to moving workbooks into production in a business environment. Book overall it was useful. I wish he spent more time explaining the ugly plumbing of implementation rather that the clean, fun world of a perfect dataset such as the superstore.

[Tiffany Valdez · Rating 5 out of 5]

If only this was published 4 years earlier! 😁
So many “aha” moments with this book. I highly recommend this if you want to get started with Tableau.

[Vicky · Rating 4 out of 5]

Ryan Sleeper was basically the first "Tableau Zen Master" whose dashboards I started following on Tableau Public, and I really admired his clean and consistent style. His blog is written in a similar clear manner.

Since this book came out in 2018, I wanted to make sure I was reading most of it in 2018, given that the desktop versions have already gone through like three upgrades since last summer. It's nice to keep a copy in my office that I pull out as a go-to reference for basics and reminders.

This book is organized into 5 sections:

- Fundamentals: introductory stuff for new users, preparing data, and the tools you find on the desktop interface, like dimension vs. measure, filters, calculated fields, parameters, sets, level of details

- Chart Types: all of this is custom, not from the "show me" options, and there are basically 28 tutorials in this section. It's good enough, but one can also find many of these online. It's nice to have a printed version, though. I ended up looking at the custom polygon map the most.

- Tips and Tricks: this is the best section imo that I would keep revisiting with helpful how-tos on efficient workbooks, device-specific layouts (that we are not supposed to need anymore in 2019), aka the kind of stuff you might learn in frustration, over time, but can shortcut with guidance

- Framework: an outline for approaching a dashboard project from beginning to the end, which is helpful to keep in mind as you are trying to seek information from multiple people, feeling fragmented in the process

- Storytelling: the only comment I have is that I mentally think of people in the "I hate Comic Sans and Pie Charts" camp (blegh) vs. "Who Cares? Comic Sans and Pie Charts Are Fine, Sometimes" camp, and I am in the latter. . .

Also to note: this book is written with the assumption that your data set is perfectly shaped before visualization, which, while I was aware of this, I still had to learn again that it is where most of the work is done. This book supported me through the initially released versions of 3-4 projects: historical enrollment, degrees awarded, course scheduling, and classroom utilization.

[Donn Lee · Rating 5 out of 5]

I cannot recommend this book enough if you're a beginner/intermediate user (which is where I started). I worked as an analyst for half my career before eventually leading a team of analysts. I've worked mostly with Excel, Access and SQL Server, and have an intermediate understanding of Power BI.

So when I switched jobs and had to learn Tableau, I found it easy to get the basics. Many of the things were similar, and visualisation concepts transferable. But I found it IMPOSSIBLE to do stuff that felt like second nature in the other tools I used to use.

This book helped me with that tremendously. Many of the things that I sought to do but couldn't I finally managed to do with the tips here. It's filled with step-by-step guides, as well as insights you only get when working as an analyst for a while.

It was also highly readable and engaging (who'd think that of a technical book?), perhaps also because I felt much of the author's career and thinking mirrored my own -- i.e. of the analyst who loves data, experimentation, and is sometimes thrown into worlds he or she isn't quite ready for yet.

[Jake Losh · Rating 4 out of 5]

This is a great book for someone who has never used Tableau before and is looking to dig deep into what you can do with it. Chapters are bite sized, practical and functional, and you should be able to apply the recipes to your data pretty easily, assuming you have clean data. Data cleaning and working with funky data are out of scope for the book, but a section on trouble shooting data structure may be a useful addition.

I would not recommend for someone with extensive experience with Tableau. That said, Part III has a lot of good tips and tricks an expert user could add to their tool kit.

[Carlos · Rating 4 out of 5]

This book is a traditional textbook heavy in text and theory. I definitely learned a lot, but the thing I dislike about these sort of books is the datasets they provide are always crisp, clean, and without issues — this is nothing like the real world where all your data is messy, unorganized, and requires a lot of preparation before you can analyze anything.

There were tips and tricks I learned that I’ll use in my day to day, but I think you could ready a much less dense book and still get the same results and skills.

[Delhi Irc]

Location: GG7 IRC, ND6 IRC, GG6 IRC, PTI IRC
Accession No: DL030126, DL030127, DL030182-85, DL030188