Clearly and Simply

All Peaks of the Alps visualized with Tableau

A Tableau visualization of all peaks of the alps including the option to find and highlight one peak or to select one by clicking on the map

The FrankensTeam runs one of the most interesting and resourceful websites about advanced charting techniques in Microsoft Excel (E90E50fx). In March 2015 the team met in person for the very first time in Milan. To celebrate this, they published an Excel workbook with a visualization of all peaks of the Alps: Meeting in Milano, trip to the Alps and an Excel chart. 

Having been a mountaineer in my younger days, I was intrigued with this idea. I asked them for permission to use the idea and data for a replica of their visualization in Tableau. They kindly agreed.

I am deeply ashamed to admit that I am sitting on the Tableau replica for a couple of years already, but never published it. Until today.

This post provides and explains a Tableau Public workbook showing all peaks of the alps with all the amazing interactive features of Tableau.

Alternative Bullet Graph Design in Tableau

How to realize an alternative Design of Bullet Graphs in Tableau

The recent posts suggested an Alternative Design of Bullet Graphs and an interactive version of a Bullet Graph. Both articles provided example workbooks in Microsoft Excel.

These posts included three variations of the well known standard design of Bullet Graphs described in Stephen Few’s design specifications: no qualitative background areas (e.g. poor, satisfactory, good), data labels for actual and target as well as the visualization of the gap (target minus actual) with a data label and a span line to put the gap label into context, i.e. a thin line between actual bar and target line with arrows at the beginning and the end.

How would this alternative design of a Bullet Graph look like in Tableau?

Well, truth be told, I never managed to create an exact replica of my Excel implementation in Tableau. The Excel version is using error bars to display the span line of the gap. A comparable feature is not available in Tableau, but you can still realize the alternative design of Bullet Graphs in Tableau coming close to the Excel implementation.

Today’s post presents a short description of how to realize my alternative design of Bullet Graphs on Tableau Public including the option to download the Tableau workbooks.

S-Shaped Function in Tableau

How to create a customizable S-shaped Function in Tableau

The speed of adoption of an innovation usually follows an S-shaped function. Such a function shows an initial exponential growth until the inflection point, followed by an exponential decay until it converges to an upper target value. In other words, a curve looking like an S-shaped pattern.

Typical examples for business measures following an S-shaped function are adoption rates of new products, market shares of new companies, the effects of new processes or new organizational practices and the like.

Providing a customizable (i.e. user-defined) S-shaped function in a Tableau workbook can be very helpful across all stages of advanced analytics: in descriptive and diagnostic analyses, the S-shaped function can be used as a customizable reference line for the actual historical development and for analyzing deviations. In predictive and prescriptive analytics, the S-shaped function can be used to model and forecast expected future developments and to perform sensitivity and what-if analyses.

Having a ready to use S-shaped function in Tableau is a must-have for your Advanced Analytics Toolbox.

Today’s post provides a Tableau workbook template with a fully flexible user-defined S-shaped function. The workbook is published on Tableau Public and also available for free download.

Solar Calculations in Tableau

How to calculate sunrise, sunset, solar noon and daylight hours for any location at any given day in Tableau

In the past few months (on and off), I have been working on a blog post providing 50+ time formulas in Tableau, similar to the article String Calculations in Tableau published in 2014.

As you can imagine, developing and especially describing 50 Calculated Fields is a lot of work and that’s why this is still in progress. But I am close.

Anyway, during the development I had the idea of providing Calculated Fields for the time of sunrise and sunset in any location at a selected day. It turned out that this is way more complicated than it may sound and I couldn’t get my head around the math. Luckily, I finally stumbled across a brilliant Excel workbook provided by the Earth System Research Laboratory with all necessary calculations and formulas. Transferring the Excel formulas to Tableau Calculated Fields was only a diligent, but routine piece of work.

Today’s short post provides a Tableau Public workbook visualizing sunrise, sunset, solar noon and daylight hours for the ~ 8,800 largest cities in the world at any given day. If you need the Calculated Fields for your own workbook, you can download the workbook from the Tableau Public dashboard published below.

Writing and Reading Tableau Views to and from Databases and Text Files – Part 2

How to use R, a Tableau connection to R and Calculated Fields to store and load the underlying data of a defined Tableau View in a Database or Text File (part 2 of 2)

This is the second part of Michael Martin’s guest post on how to use Tableau and R to read and write the underlying data of a Tableau view from / to an ODBC database.

Michael is the Managing Partner at Business Information Arts, Inc, Tableau Partner, Tableau Certified Consultant, Tableau Instructor and leader of the Toronto Tableau User Group.  Last, but not least, Michael is the only person I know who is using Tableau Software since version 1.0.  

NOTE: You may need to zoom into some of the screen shots below for legibility reasons. Also, the text below contains references to the "Level of Detail Shelf".  This is synonymous with the Detail Pill in the Tableau Marks Card within the Tableau 9.x and 10.x user interface.  As mentioned in the introduction to part one of this post, including a '$' character as part of an RODBC object name (for example crs$odbc, crs$odbc.tables, crs$dataset) could cause an error on your system, and the affected calculation will fail.  If this happens, replace instances of $ within an RODBC object name with another character within the affected calculation, such as an underscore - i.e. _.

Supporting files and a README file are available for download at the end of this part of the post. Please look at the README file first.

The author would like to thank Leonid Koyfman for his suggestions.

The first part of this post walked you through the process of

• downloading and installing R and RStudio
• installing the required R packages,
• setting up the ODBC database connection
• writing the Calculated Fields in Tableau to read the underlying data of a Tableau view from a database

In the first part, we have only run SELECT queries, but we could also run INSERT, DELETE, UPDATE or INSERT INTO (Append data) queries – all we need to be is pass a valid SQL statement to a Calculated Field that establishes an ODBC connection to the Database and run the SQL statement.

Today’s second part of the post will

• show how to insert data of a Tableau view into a database
• demonstrate the necessity of aligning the orientation of the view and the Table Calculation
• show how to perform data definition queries
• provide the general caveats of the technique
• demonstrate an analysis technique that leverages multiple exports of a Tableau View based on the Superstore Dataset to SQL Server
• give some insights on performance and upper limits
• provide some useful links regarding the integration of Tableau and R