Tableau is one of the biggest data visualization tools around. Learn more about Tableau—as well as how data analysts use it—in this guide.
If you’re new to the world of data analysis and business intelligence, you’ll quickly find there are a lot of new words and processes thrown at you on a daily basis. It won’t be long until Tableau becomes an important word in your vocabulary. What is Tableau, exactly? We’ll go over that in this post, as well as looking at the different ways that data analysts use it. Want to skip ahead? Just use the clickable menu.
- What is Tableau?
- What are the Tableau products?
- How do data analysts use Tableau?
- Key takeaways and further reading
With that, let’s proceed.
1. What is Tableau? A brief history
At its core, Tableau is a data visualization tool, founded by three Stamford students as a result of a computer science project in 2003. Tableau was created with a guiding philosophy to make data understandable to ordinary people.
It’s considered to be the most popular visualization platform in the industry, well regarded within the business intelligence community for its ease of use and simple functionalities, which make it easy to create insightful dashboards in a few clicks. It is an end-to-end platform, designed with both data analysts and business users in mind.
2. What are the Tableau products?
Tableau has a wide range of products that support the user through the entire data analysis process, from data preparation to sharing, with governance and data management support along the way. Tableau makes new releases on a quarterly basis, with updates and patch releases on a regular basis.
Some of the Tableau products include:
- Tableau Prep is a visual interface that cleans, combines, shapes and transforms data. It makes it easy to pivot data, remove empty fields, replace fields and merge fields from different data sources.
- Tableau Desktop is used to connect and explore data. This connects to any data format including Excel and web APIs. You can then explore the data using the visual system. Analysts and business users can explore data and build reports and dashboards, which can be shared out across the organization.
- Tableau Public is free and has all the features of Tableau Desktop, with the caveat that you can only share your reports and dashboard to Tableau Public (Google docs of Tableau). New users can use Tableau Public to see how other reports and dashboards are created and learn from them.
- Tableau Server is an online server that allows data analysts to use all the functions of Tableau, without having to download and open workbooks to use on Tableau Desktop. With Tableau Server, an administrator can also set permissions on projects, workbooks, views and data sources.
- Tableau Online is the Tableau platform hosted in the cloud. Users and customers alike can access and explore visualizations and data. One advantage of Online is that you never have to install or manage software.
- Tableau Mobile makes reports and dashboards accessible by users on the go through either an iOS or Android app.
Now that we’ve got an understanding of what Tableau is, how it came to be, and some of its core products, let’s have a look at how it’s actually used by data analysts in their work.
3. How is Tableau used by data analysts?
Put simply, Tableau is popular with data analysts and their colleagues for its ease of use. Once a dashboard is created, users are able to interact with the data to get varying insights, which then lead to being able to make informed decisions and targets for the company.
The Tableau user interface is intuitive, performing complex data visualization processes by simply dragging and dropping. It is a dynamic platform with new features being added regularly, meaning that there are always new ways of making use of data.
That being said, we’ve listed some of the more common use cases for Tableau that have been around for a while.
- Data prep and cleaning: Using the built-in data connections and tools in Tableau Prep, analysts are able to work more efficiently, even when collating data from multiple sources and file types. Additionally, files with the same column names can also be combined into one data source, saving time on copying and pasting. You can learn more about data cleaning in this guide.
- Connecting and exploring data: Tableau’s drag-and-drop interface is intuitive and dynamic, allowing for more flexibility and experimentation. Visualizations can be built out rapidly with the aid of the Show Me feature, which switches between a variety of chart types and creates a view in a few clicks. This removes the need to reformat data for each chart type or to spend time formatting and aligning items.
- What-if analysis: The drag-and-drop interface, coupled with Tableau’s powerful input capabilities (no row or column limits!) allow data analysts to modify calculations and test different situations with ease.
- User interactivity: Dashboard users are given the opportunity to interact with the dashboards created by data analysts and customize them at-will. Of course, the data analyst creating the dashboard will set parameters for the user to work within, but there is a lot of flexibility available here.
- Calculations and functions: The robust calculation language in Tableau makes it easy to perform sophisticated calculations and statistical functions. Anything from basic aggregations to statistical calculations (including covariance and correlation) can be achieved by working with the intuitive interface.
- Community collaboration: Through Tableau Public, there is an active community which allows for data analysts and other interested users to collaborate and learn from others. Product upgrades and patches, as well as new products, are added on a regular basis based on customer feedback.
4. Key takeaways and further reading
By now, you hopefully have a good understanding of Tableau, its key functions and products, as well as how data analysts use it. It’s important, however, to remember that Tableau is not the be-all and end-all of data visualization—in fact, there are many data visualization platforms on the market.
While Tableau is one of the better-known platforms, the best platform for your data will depend greatly on the needs of your organization. Many platforms, including Tableau, will allow for free trials on some of their products, so that you can work with it a bit before committing to one platform.
Learn more about data analytics with this free, 5-day data analytics short course, and check out the following posts for more insights on data visualization: