Freakalytics®

Practical Analytics for Better Decisions

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Bringing clarity out of an infographic, “Income Inequality in the US” from Mother Jones

A colleague shared this Mother Jones infographic, which attempts to explain the disparity in income between richer and poorer families in the US.  The data is indeed fascinating, but quite difficult to read in their flashy infographic.

There are two major issues that hinder understanding when viewing this infographic:

1) Using areas of circles to encode the incomes is very difficult for most people to interpret.  Additionally, with the difference in income being so large, it is nearly impossible to fit this on a normally sized web page.  The largest group, the yellow circle, is mostly cut off in their infographic.

2) The infographic is overloaded

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Create data-driven groups in Tableau with data blending (VLookup)

Similar to VLookup functionality in Excel, you can use a second data source to dynamically create a new group in a separate Tableau data source. Just follow along with this example to create one.

1. Open the Tableau included sample data source, Sample – Superstore Sales (Excel)

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2. Map Sales by State: CTRL-Click on State and then on Sales.  Click Show Me and select Symbol Maps.  A map will appear.

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3. Suppose you would like to label each state by region and/or filter by region.  If you already have a text file, Excel spreadsheet or database table with region data, you can use this for an Excel VLookup type of functionality.  The example

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Everyday analytics, “The Accidental Analyst”

 
Tableau 8 for The Accidental Analyst®—two-day workshop
      Seattle, Washington May 9th-10th
 
 
 
 Order “The Accidental Analyst“
      Amazon US
      Amazon UK
      Amazon Deutschland
 
 
Are you drowning in a sea of data? Would you like to take control of your data and analysis to quickly answer your business questions and make critical decisions? Do you want to confidently present results and solutions to your managers, colleagues, clients and the public? Are you a champion of analytics in your organization helping others learn how to analyze and make sense of their data?

If so, The Accidental Analyst: Show Your Data Who’s Boss is for you! Although you didn’t plan for a career as a data analyst, you’re now in a position where you have to analyze data to be successful. Regardless of the software package that you use, we’ll walk you through a clear, step-by-step framework using illustrated examples to help you understand and apply the analytic process to find answers to real-world questions. We call this flexible framework The Seven C’s of Data Analysis.

Read this book for inspiration, ideas and confidence to begin tackling the problems you face at work. Keep it by your desk as a reference on how to organize, analyze and display your data. Throughout the book, we also include expert tips, tricks, and shortcuts that took years of analyzing data to discover and understand!

Order your copy of “The Accidental Analyst” at Amazon US, Amazon UK or Amazon Deutschland.

Reviews
“This is a wonderful book, filled with practical advice.
Business people who are struggling to make sense of their data
will find it accessible and directly applicable to their work-
a great resource for building analytical prowess.”
Stephen Few
Best-selling author, “Show Me the Numbers” and “Now You See It”

“Finally, a book that clearly explains the fundamentals of business analytics!
I wish that I had this book at the start of my career as a data analyst.”
Tim Latendress
Financial Analyst

“This book is an amazing resource for regular business people
who want to make sense of their data and take charge of their business!
It provides simple yet comprehensive coverage of business analytics.”
Diego Saenz
President, Petplace and former CIO of Pepsi Latin America

“… the executive manual, like an Executive MBA” for knowledge workers…
Ted Cuzzillo, DataDoodle
The Data Warehouse Institute, BI This Week Newsletter

Pat_Hanrahan_on_The_Accidental_Analyst_at_Tableau_Customer_Conference

In his only talk at the 2012 Tableau World Conference, Pat Hanrahan discussed our book, The Accidental Analyst, as a foundation of his presentation. He said our book changed how he thought about analytics and inspired him to change his approach to teaching courses at Stanford.
Pat Hanrahan, PhD
Canon USA Professor at Stanford University
Co-founder of Tableau and Pixar
Pat has two Academy Awards

 
 
Tableau 8 for The Accidental Analyst®—two-day workshop
      Seattle, Washington May 9th-10th
 
 
 

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Rapid Graphs with Tableau Software 7 now available on Amazon, Kindle and Nook


Buy the Kindle version at Amazon, just $9.97! (free preview)

Buy Nook book at Barnes & Noble, just $9.97! (free preview)

Buy the print version at Amazon US, UK, Germany,
France or Spain (only in English, regardless of source country)

International shipping alternative to Amazon

Still using Tableau 6? Yes! You can buy the 6 version!

Tired of boring spreadsheets and data overload from confusing graphs? Master the art of rapid graphs with Tableau! Tableau is designed with one goal in mind, to give you the power to quickly explore and understand your data so that you can make informed decisions in a wide variety of real-world situations. After learning Tableau, you will be able to communicate your findings with audience-friendly graphs and tables.

“A picture is worth a thousand words” is a common saying that is more relevant today

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Tableau customer profile, Eystein from Norway, Banking & Insurance

Tableau customer profile: Eystein from Norway

Customer
Eystein from Norway

Favorite quote speaking with him
“Make it simple and fast, my IT team was cheering on Tableau after trying it and QlikView.  They really hoped we would pick Tableau and I am very happy we did.”

Situation
Eystein recently took over a BI team that wanted to accelerate use of data across every area of the bank and subsidiaries.  The bank and subsidiaries are heavy users of SAS Enterprise Guide, SAS Web Report Studio and SAS Enterprise Miner. 

They have a variety of data sources and data marts throughout the business.  There is also a centralized Enterprise Data Warehouse (EDW) effort that is making headway, but has a long list of items ahead of them.  In the meantime, SAS users are rapidly creating new data pulls that Eystein would like to use in Tableau.  He realizes that the EDW team will never be able to have all the data that is needed by the business, so SAS is a good platform to prep the data for widespread analysis in Tableau.

Status

They recently evaluated fast analytic tools from

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Detailed review of Tableau Data Blending by a PhD Student at UW- Seattle

 

Detailed review of Tableau Data Blending by PhD Student at UW- SeattleFrom the article conclusions:

“Data blending is a new feature in Tableau that simplifies the process of integrating data from a variety of heterogeneous sources. We presented several compelling customer applications that leverage the feature and highlight its usefulness for interactive visual analysis. Additionally, we are engaging with our customers to improve the flexibility and capabilities of the feature. Ultimately, our goal is to make it easier for users to discover and combine data that will help them in their exploratory analysis.”

If you are a data enthusiast who actually enjoys data management and warehousing, you will find this article fascinating and informative.

However, if you are still learning Tableau and want to understand this and related features, here is an excerpt from the section on Data Blending in our book, Rapid Graphs with Tableau Software:

“A common reality for many users of Tableau is that their data is stored in multiple systems, such as Excel, Access, CSV files, Oracle databases and many other database systems. Early versions of Tableau <!–more–>allowed you to connect to multiple data sources at one time in the same workbook, but NOT in the same view. In other words, if you had budget data in your Excel data source and actual spending data in Oracle, you had no automated way to make a view comparing budget with actuals. Recent versions of Tableau allow you to blend your data to help you solve similar problems.

The following example uses the Country Blending …”

To download the article, “Dynamic Workload Driven Data Integration in Tableau” by Kristi Morton, Ross Bunker, Jock Mackinlay, Robert Morton and Chris Stolte, click here.

To learn how to use Data Blending in Tableau and create great analysis quickly, preview Rapid Graphs here.

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Quick and dirty analysis with Tableau 6 (in thirteen lucky steps)

6_Manual_Rearrange_Items_Freakalytics_1_TableauLet’s face it: in the daily world of work, you often are asked to provide an answer to a new problem in less than a day. Of course, your boss tends to forget about the other three project deadlines you are currently facing, so you really have only 10 or 20 minutes to squeeze in a quick and dirty analysis. 

If this sounds familiar to you, this cheat sheet includes thirteen flexible steps that can take you from being clueless to looking smart in just a few minutes, with a little help from Tableau. Hopefully you’ll be able to obtain enough information to come up with ideas for an e-mail update or talking points for the unexpected meeting that is looming large over your day, showing your boss and colleagues that you can deliver great results in time to be useful. 

So, if you’re already a user of Tableau, this cheat sheet will guide you to do the analysis. Even if you are totally new to Tableau, you can see the possibilities of what you can accomplish in a short amount of time, once you get started.

Download a printer-friendly version of this article here.

1 What question will you examine?

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Okay, in reality this step might take hours or even days! But let’s assume you have your question, and if it is complex, break it down into several, simpler questions.

2 Grab the closest, readily available dataset that is relevant

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Top Freakalytics articles of 2011

#5 Examining data over time (7 ways with Netflix stock prices)

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#4 Bullet charts & enhancements: making Stephen Few’s invention even better

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