Tableau Public

Ranking Banks by Number of Complaints

I recently downloaded a dataset from the Consumer Finance Protection Bureau (CFPB) in order to construct a handy visualization. The CFPB maintains a database that houses a collection of complaints on a range of consumer financial products and services that are sent to companies for a response.

Per the CFPB, “the database also includes information about the actions taken by the company in response to the complaint, such as, whether the company’s response was timely and how the company responded.”

Although the database is updated daily, I chose to visualize information from the complete year of 2017. In fairness to the financial institutions, company level information should be considered in context of company size and/or market share.

Financial institutions analyze this information frequently as a way of understanding and continuously improving their customer service.

I highly recommend “The Big Book of Dashboards” by Jeffrey Shaffer, Andy Cotgreave and Steve Wexler. The book contains a number of visualization examples that provide guidance on dashboard creation for any number of business use cases. In this Tableau Public dashboard I relied heavily on the visual guidance for their Complaints Dashboard as you can observe.

Screen Shot 2018-06-03 at 10.02.14 PM

Complaints Dashboard from “The Big Book of Dashboards”

Click on the picture link to view the dashboard on Tableau Public (not optimized for mobile).

Dashboard 1

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Coursera Review: Creating Dashboards and Storytelling with Tableau

Discounts Harm Profits

I recently finished the “Creating Dashboards and Storytelling with Tableau” course on Coursera. The course was taught by adjunct faculty at the University of California Davis. Although it is the fourth course of five in the “Data Visualization with Tableau” specialization, it is only the third course that I have taken. I skipped the very basic first course and will concentrate next on finishing the capstone. 

If you do take this course be prepared to put in a fair amount of work on weeks three and four when the dashboard and story project are respectively due. I put in at least five hours of effort on each individual assignment not including watching videos, reading materials and taking quizzes.

I found the storytelling course to be informative and worthwhile. Unlike a Udemy course on Tableau that wades right into the applied aspects of clicking and dragging items, Coursera courses offer more of an academic background on the subject matter.

The point of this course is to hammer home that stories provide context and meaning that can’t be matched by a list of facts. We’re informed that stories engage more of your brain than simply absorbing a list of facts.

We learn that you should always try to make your stories relatable to the viewer so that they personally connect or identify with some aspect of the story. You should find a specific story of a person who exemplifies the larger narrative rather than starting with a lot of general facts and figures.

Politicians employ this tactic all of the time. Instead of spouting off a list of facts about their particular issue, the politician will first paint a picture regarding Joe the small businessman or Jill the single mom. They’ll then discuss how legislation (or lack thereof) will affect their constituents particular situations; in the hope that the listener will relate to the individuals. This is an exercise in using the particular to illuminate the general.

Here are a few of the tips I learned in regard to telling stories with data:

  • Use time based trends and consider a line or bar graph depending upon the data;
  • Use rank ordering (e.g. use a bar graph to rank salespersons by sales);
  • Use data comparisons where appropriate (e.g. polling data showing candidate support over a period of time);
  • Use counter intuitive visualizations (e.g. most people are surprised to learn that the United States has the highest incarceration rate by far amongst OECD countries);
  • Tell stories through relationships (e.g. use scatterplots to illustrate the relationship between sales and profits);
  • Check your facts;
  • Focus on a key statistic or intriguing piece of information;
  • Make your story insightful; don’t leave the audience guessing on what you want them to take away form your presentation;
  • Make your story relatable;

By all means check out my submission for the final project. I illustrated the relationship between discounted orders and profits to show that discounted orders are by far less profitable. This was accomplished by creating a set in Tableau to identify all discounted orders.

Until next class!

See also:

Coursera Final Assignment: Essential Design Principles for Tableau

Coursera Final Project: Data Visualization and Communication with Tableau

Coursera Final Assignment: Essential Design Principles for Tableau

Dashboard 1

I recently completed Essential Design Principles for Tableau offered by the University of California Davis on Coursera. I’ll offer some review commentary. I thought it was a solid class as it covered data visualization concepts such as pre-attentive attributes and the Gestalt principles. This class was a bit more heavy on the conceptual side of the house as opposed to delving into practical Tableau instructions. However, there are other classes in the specialization that have a more hands on practical approach.

In this assignment we had to highlight the three worst performing product Sub-Categories in each region. Additionally, we had to demonstrate how these worst performers compared to other product Sub-Categories in their respective regions. Finally, the visualization had to highlight the three worst performing Sub-Product Categories overall with a color emphasis. The scenario given to the class was that a sales manager had to cut the three worst performing Sub-Categories in her region and needed a visualization that addressed her concerns.

Guidance was not provided on how to identify the three worst performing categories. Some people in the class simply used profit as their key performance indicator (KPI) which I think is misguided. You learn in business (or business education) that profits do not equal profitability.  From Investopedia:

Profitability is closely related to profit, but it is the metric used to determine the scope of a company’s profit in relation to the size of the business. Profitability is a measurement of efficiency – and ultimately its success or failure. It is expressed as a relative, not an absolute, amount. Profitability can further be defined as the ability of a business to produce a return on an investment based on its resources in comparison with an alternative investment. Although a company can realize a profit, this does not necessarily mean that the company is profitable.

For these reasons I used the Average Profit Ratio of the products in each Sub-Category as my KPI as opposed to raw profits. If you had to sell $100,000 of product A to make $1,000 in profit (1% profit ratio), would you eliminate product B which requires $1000 in sales to generate $500 in profit (50% profit ratio)? Only if you want to go out of business!

In order to complete the visualization you see above on Tableau Public I had to incorporate nested sorting principles and also highlight the three worst performing elements on a bar chart. Luckily for you, I have videos that will demonstrate how to accomplish these tasks.

You can check out the rest of my videos on my Youtube Channel or find them on this site under Videos.