The Tableau Workshop: A practical guide to the art of data visualization with Tableau

How hard the contents are? But that’s a personal issue

From the start, the book provides a highly organized structure. Each chapter has an overview that acts like an appetizer for the reader. This overview includes learning objectives. These elements combined offer a pedagogical approach to the book. The chapters are easy to read, there is good flow of content, and each topic is fairly comprehensive. The examples are relevant and I particularly enjoy the exercise approach that gives the reader the opportunity to dive into the tool with guidance. I also appreciate the notes that let the reader know which combination keys to use for an Apple vs a PC.I was selective in my reading and went through the first five and then seven, eight, and nine. The first chapter, in particular, does a good job at setting the groundwork and provides a solid overview of the Tableau, the different iterations such Public vs Online vs Desktop, and how and when each should be used.I really appreciate the inclusive approach in incorporating Tableau Prep, which may be particularly helpful to those who need to prepare and clean their data prior to loading to Desktop. Chapter 3 provides a lot of information and plenty of hands-on exercises as well as activities that readers are encouraged to engage with to get the full benefit. Chapter 4 covers data exploration in moderate depth, acting as solid foundation to Chapter 5 that illustrates distributions and relationships. What I like particularly about Chapter 4 is the effective use of examples and the detailed activities that guide the reader through the key components. The chapter goes through three major chart types: stacked bar charts, pie charts, and treemaps, which are the basic foundational charts. The authors do a good job about setting expectations here and they put forth questions like “Why is this step being done, and can I improve the method?” These are questions that any data analyst must consider. I also appreciate the variation in charts used here and the real-world scenarios as well as the “words of caution” for certain charts. Chapter 5 is focused on dual axis, histograms, box and whisker plots, and scatter plots, as well as reference lines that help the reader understand when to use each type for distributions or illustrating relationships.Overall, the authors do a good job at illustrating the various parts of the main tool of reference, Tableau Desktop. There is some room for improvement with regard to defining a few items that were referenced. The user may benefit from this. For example, the author explains what “Dimensions” are and refers to categorical, descriptive, and qualitative properties. I would have like to have seen a little more explanation on these properties. I recommend the reader approach this book more as a “How-To” or even a Cookbook. I believe it properly covers the topic of how to use the software itself rather than aspects of data visualization in general. It is a practical guide that any novice may learn a lot from.

Great book but the view is very small in Kindle Reader. The book won't widen to fit the screen and the pictures are tiny.

After having reviewed and advance copy of this book I can honestly say that it is just the sort of guide I would have wanted five years ago when I began my journey with Tableau. I suspect like at least some of you reading this review you’ve done like me and spent your time learning about Tableau in at least some of the following ways:1. Tableau Forums2. Documentation in Tableau itself3. Reverse-engineering others’ work4. Trial and error (I’ve done A LOT of this one)5. Online videos from YouTube, LinkedIN, TableauYou’ll see that none of those include “book” and so I approached this review being a bit skeptical. I will say that there is still always the risk that as Tableau adds new features at a rather rapid pace you find that over time this particular version of the book will become dated, and the writers will need to either publish addendums or an entirely new version. In either case if they do the same sort of thorough job they did with this version you would do well to spend the bit of money to keep current by having the latest version in you Tableau learning toolkit.All of that said here are the things I appreciated about this book.There was a nice bit of coverage of not just the how to accomplish tasks in Tableau (for which there are so many ways to do things) but there were also nods to the processes that a developer might follow in order to get to the point of starting a project. This asks the developer to think about the types of questions they might being asked to help answer in advance of their analysis.Tableau Prep. Prep always seems to me to be somewhat of the forgotten third child of the Tableau world (with Desktop and Server getting so much more attention). The fact that this includes Tableau Prep makes it a lot more valuable.The one major miss (and there really is just this one) is any real coverage of the new “Relationships” feature. There is coverage of joins and blends, but Relationships are so much more powerful than either it would seem to me to be better to spend more effort on that (and maybe less on LoD calculations) which can be less important if you are using Relationships. As it stands, there is just a link to Tableau’s documentation on the topic along with a note that in version 2021.4 and later the process may look different. Since I am writing this review in the year 2022 and there is already a 2022.1 version available, I will simply refer this review reading back to my previous comment about how this is a book and books become dated over time.The remaining chapters do a fine job of taking even the novice user through how to create explorations and analyses. These topics can be covered by any of the five resources I note above but having them all in one book a new Tableau developer can keep at the ready (or even work through as part of a just-in-time learning process) is where you’ll see the benefit from this purchase.

As a rising Data Scientist, I have been interested in the field of data visualization and explored tools including Tableau, Microsoft Power BI, Looker/Google Data Studio, and Excel. I have frankly found Tableau much less intuitive than Power BI, but certainly powerful and packed with useful functionality.Enter "The Tableau Workshop." This book overlooks NO detail on how to properly set up projects, connect (multiple) data sources, and put your data viz to work. It goes into depth on a variety of data joins, aggregations, and transformations, and has a great section on custom SQL querying. (Personally, I would recommend practicing data professionals perform many of these actions upstream before working with a visualization tool, but it's certainly possible and reading through this will broaden most anyone's horizons.)As you might expect from a book on data visualization, this work is packed with example graphs and I appreciate the breadth of the curated selection inside. Find inspiration in less-familiar ideas like tree-maps, area charts, and charts with stacked variables, as well as the usual suspects of line and bar graphs. And again, this book will spare no detail on how to utilize Tableau Desktop and more to export and present your finished work in a variety of formats and contexts.