Last year I started lecturing a Data Analytics course at university (as part of an MBA program). In the meanwhile, I was refining the list of books that I highly recommend to read. Three of these books form the Data Journey!
What is the Data Journey?
The Data Journey is a human-focused approach to understand the evolution of data storytelling, the power of visual analytics, and the impact of data from real-world business scenarios.
1. Info We Trust: How to Inspire the World with Data
We start our Data Journey with the book Info We Trust. This book examines all parts of the data storytelling lifecycle across disciplines. The use of marginalia and hand-drawn illustrations give you both simple lessons to take away, and insights into where to find out more. The book is full of magnificent references that inspire further reading.
Now it’s time for hands-on. Visual Analytics with Tableau covers everything you need to get started with Tableau (students get Tableau for free!). The book guides you from the first steps of connecting to data, creating different types of charts, and adding calculation fields to more advanced features such as table calculations, forecasts, and clusters, as well as R, Python, and MATLAB integration for sophisticated statistical modeling.
3. The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios
Back to business (as this course is designed for an MBA program). We close our Data Journey canon with The Big Book of Dashboards. This is a comprehensive reference book with real-world solutions for business dashboards and detailed analysis of do’s and don’ts. The examples in this book are well-organized and categorized by industry and functional business areas.
[Update 10 July 2019]: Do you need more inspiration?
#MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time
Because vizzing alone is only half the fun, you should not miss the #MakeoverMonday book. Eva Murray and Andy Kriebel are icons in the data visualization community (read the interview!) and they have curated the thousands of visualizations from the #MakeoverMonday project into a practical guide that will take your design and data communication skills to the next level!
Visual Analytics with Tableau is on stock again: Screenshot shows availability on amazon.com
Did you get your Tableau Conference Europe 2019 ticket and now need something to read for the journey?
Then I have some good news: Right on time, just a few weeks before TCE19, my new book Visual Analytics with Tableau is in stock again!
As you know from my previous Tableau Conference sessions and blog posts (TC18, TC17, TC16), I love social media! So thank you for your likes, shares, retweets…
A 4-COLOR JOURNEY THROUGH A COMPLETE TABLEAU VISUALIZATION FOR NON-TECHNICAL BUSINESS USERS
Tableau is a popular data visualization and analytics tool favored by financial analysts, marketers, statisticians, business and sales professionals, data scientists, developers, and many others who need to explore insights and present visual, easy-to-understand data. Visual Analytics with Tableau is an accessible, step-by-step introduction to the world of visual analytics. This up-to-date guide is ideal for both beginners and more experienced users seeking a practical introduction to the fields of data analysis and visualization. Through hands-on examples and exercises, readers learn how to analyze their own data and clearly communicate the results.
This guide covers everything you need to get started with Tableau, from the first steps of connecting to data, creating different types of charts, and adding calculation fields to more advanced features such as table calculations, forecasts, clusters, and R, Python, and MATLAB integration for sophisticated statistical modelling. User-friendly instructions for existing options within the Tableau ecosystem–Tableau Desktop, Tableau Prep, Tableau Server, Tableau Online, and Tableau Public–enable you to integrate, clean, and prepare your data and share your work with others. Visual Analytics with Tableau:
Covers the newest versions of Tableau 2018.3 and 2019.1 plus Tableau Prep, Tableau’s brand-new data integration application
Requires no background in mathematics nor any programming experience
Focuses on the visual analytics functionality of Tableau rather than complex statistical programming
Offers expert guidance from popular Tableau Germany employee and visualization expert Alexander Loth
Discusses advanced Tableau functionality and working with different data structures
Provides easy-to-follow instructions, full-color illustrations, learning tools, online resources, and more
If you’re getting started with visual analytics and Tableau, this book will teach you everything you need to know to build the foundations and understand how and why to explore your data visually. Alexander has created a fantastic resource that guides you step by step through the process of preparing your data, using Tableau Desktop to analyse it and finding insights. –Eva Murray, Head of BI and Tableau Zen Master at Exasol
If you’re keen to go from beginner to expert in Tableau, Alexander’s excellent book gives you everything you need to know. With a crisp and clear style, he talks the reader through all aspects of Tableau, from data cleaning through data analysis and into sharing insight with others. –Andy Cotgreave, Author of Big Book of Dashboards and Technical Evangelist at Tableau Software
Visual Analytics with Tableau – an easy to understand book by Alexander Loth, one of Tableau’s very first employees based in Germany, a recognized speaker on countless conferences, and a Tableau Jedi. It contains both the basics and advanced Tableau features. If you ask me: there is nothing more you need to get started with Tableau! –Klaus Schulte, Professor at Münster School of Business & 2019 Tableau Zen Master
Thank you all who helped me to complete this book!
Screenshot of Tableau 4.0 analyzing High Energy Physics Data at CERN
About a year ago, I had a first try with Tableau and some survey data for a university project. Last week, I finally found time to test Tableau with High Energy Physics (HEP) data from CERN’s Proton Synchrotron (PS). Tableau enjoys a stellar reputation among the data visualization community, while the HEP community heavily uses Gnuplot and Python.
Tableau 4.0: Connect to Data
I was using an ordinary CSV file as data source for this quick visualization. Furthermore, Tableau can connect to other file types such as Excel, as well as to databases like Microsoft SQL Server, Oracle, and Postgres.
I’m also quite impressed by the ease and speed with which insightful analysis seems to appear out of bland data. Even though your analysis toolchain is script-based (as usual at CERN where batch processing is mandatory), I highly recommend using Tableau for prototyping and for ad-hoc data exploration.
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