Using Tableau for Data Science

What is Tableau?

Perhaps you’ve heard a growing buzz in data science circles about Tableau. The Seattle-based software firm got its start at Stanford University in 2003 and launched an initial public offering in 2013.

Tableau’s mission is to make spreadsheets, databases, and other information sources simpler for the average person to use. Co-founders Christian Chabot (CEO), Pat Hanrahan (Chief Scientist), and Chris Stolte (Chief Development Officer) began by combining a structured query language for databases with a descriptive language for rendering graphics.

The result? A database visualization language called Visual Query Language or VizQL. VizQL underlies Tableau’s eponymous software application, which queries relational databases, cubes, cloud databases, and spreadsheets, and then generates a variety of graph types. These graphs can be combined into dashboards and shared over a computer network or the internet.

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CWRU Data Analytics Boot Camp

CWRU Data Analytics Boot Camp is a rigorous, part-time program that prepares students with the fundamental skills for data analytics and visualization. Through hands-on, in-person instruction, you’ll cover a wide range of topics and graduate ready to apply your skills in the workforce.

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Columbia Engineering Data Analytics Boot Camp

Are you ready to become a data-driven professional? Columbia Engineering Data Analytics Boot Camp is a challenging, part-time bootcamp that equips learners with the specialized skills for data analytics and visualization through hands-on, in-person classes.

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Berkeley Data Analytics Boot Camp

Turn data into actionable insights. Berkeley Data Analytics Boot Camp is a dynamic, part-time program that covers the in-demand tools and technologies for data analytics and visualization through rigorous, project-based classes.

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Georgia Tech Data Science and Analytics Boot Camp

Expand your skill set and grow as a data scientist. Georgia Tech Data Science and Analytics Boot Camp covers the skills needed to analyze and solve complex data analytics and visualization problems.

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The Data Analysis & Visualization Boot Camp at Texas McCombs

The Data Analysis and Visualization Boot Camp at Texas McCombs puts the student experience first, teaching the knowledge and skills to conduct data analysis on a wide array of real-world problems. Students dive into a comprehensive curriculum, learning how to collect, analyze, and visualize big data.

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USC Viterbi Data Analytics Boot Camp Affiliated with Trilogy Education Services

Expand your skill set and grow as a data analyst. This program covers the specialized skills to be successful in the field of data in 24 weeks.

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Today Tableau boasts more than tens of thousands of customer accounts, including Red Hat, Nissan, Whole Foods, and Verizon. Allrecipes executives are using Tableau to develop a 360° view of consumers. More than 600 employees at Cornell University perform analysis with Tableau: They manage contributor relations, visualize faculty salary statistics, and track which students are in which classes. Tableau helps Zillow provide self-serve business intelligence that empowers business owners to answer their own questions.

Tableau currently offers four main products:

  • Tableau Desktop — “fast analytics for everyone” — allows you to explore and visualize data in minutes, connecting to data and performing queries without ever writing a line of code.
  • Tableau Server — “collaboration for any organization” — allows users throughout an organization to access live interactive dashboards in a web browser or on a mobile device.
  • Tableau Online — “business intelligence in the cloud” — is a hosted version of Tableau Server that requires no set-up.
  • Tableau Public — “for public data” — lets you read files saved in Tableau Desktop.

Tableau for the Data Scientist?

Given that Tableau aims to make analytics easy for analysts, executives, IT, and everyone else, data scientists may view the software as, at best, beneath them and, at worst, a threat to their livelihood.

Second point first. Popular and powerful as it is, Tableau is but one of many pieces of software used to glean insights from data. So even if everyone from the corner office to the reception desk is proficient in Tableau soon, plenty of programs will remain under the near exclusive purview of the data scientist.

So perhaps the aspiring data scientist should just leave Tableau to the amateurs? Think again. Tableau software complements such data science standbys as R and Python. While Tableau is not the best tool for cleaning or reshaping data, and its relational model doesn’t allow for procedural computations or offline algorithms, it does excel at data exploration and interactive analysis. Tableau even offers courses for data scientists looking to make use of the software.

Interested in a different career? Check out our other bootcamp guides below:

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Learn Tableau

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Online BSc Data Science and Business Analytics

The online BSc Data Science and Business Analytics from the University of London, with academic direction from LSE, enables students to build essential technical and critical thinking skills and prepare for careers in data science, analytics and other growing fields – while they work, without relocating.

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Sold on learning Tableau, or at least checking it out? You could be up to speed in as little as a few weeks thanks to Tableau’s training options, including:

  • On-Demand Training: Learn online and at your own pace with free recorded sessions that cover everything from connecting to data and creating views to administering Tableau Server and building funnel charts.
  • Live Online Training: Scheduled to cover a specific topic at a set time, real-time online learning sessions promise to make you a “Tableau pro.” You have to register for these instructor-led sessions, but they’re free.
  • Classroom Training: Tableau offers instructor-led classroom training across the globe, on-site or in a virtual classroom.

If you’re the bookish type, you might consider Tableau Your Data!, which goes beyond the basics of Tableau Desktop’s interface and explains best practices for creating effective visualizations for specific business intelligence objectives.

Last updated: June 2020