I wanted to provide a bit more information and resources about Tableau from my presentation before break. Ideally, I would have liked to provide a mini-lesson with the purpose of learning basic skills in Tableau, but I hope this blog posts provides a better understanding of what Tableau is and how it is used.
What is Tableau?
Tableau is a very powerful software used as an analytical tool to identify trends patterns etc. Tableau takes data visualization to a new level by communicating large amounts of data in an aesthetically pleasing format.
Why is Tableau Important Anyways?
Tableau is being used more and more by companies for reporting and analysis as it can handle large amounts of data while still maintaining a user-friendly format.
In addition, Tableau offers features such as Tableau Online and Tableau Server which allow users to upload their content to the Cloud allowing for access to reports mobile devices.
How Does Tableau Work?
Tableau connects to a data source or a data extract. An example of a data source would be something like Salesforce, Azure, or even R. A data extract would be something like an Excel spreadsheet.
Once the data is connected to the data, sometimes the data will need to be cleaned or organized. Larger firms that have successfully integrated Tableau often have pretty clean data which require little to no cleaning. However, it's a much different story for smaller companies or firms that have just started using Tableau.
What do I do with the data?
Once you've connected and cleaned your data, it's pretty easy to get started creating content. I often compare Tableau to PivotTables on steroids because Tableau has the functionality of PivotTables, but it is much more powerful and you can use it for very large amounts of data. The image below shows the starting interface you see when you begin a workbook.
Like anything, it requires practice and constant use of Tableau in order to build complex dashboards and visuals that are both informative and aesthetically pleasing.
I've linked a few great resources below that include a free-trial, and an introductory video that walks through a basic how to on Tableau as well as a viz gallery with examples of how Tableau is used and how complex dashboards can get.
Free Trial @ https://www.tableau.com/products/trial-link-old
Video & Data Download (You may have to enter a few details such as name etc. to access video, but once you do navigate to the bottom of the page and click the Download link under Data Sets)
Viz Gallery - A library of top-notch data visualizations
Hey Shivani! Thanks for posting this. I love learning about new programming languages. This is most appealing to me because the format is very user friendly but also able to truly analyze data. I also appreciate Tableau Online and Tableau Server for Cloud utilization which makes it easier to continue working when "off-site," not at work. Also working in the financial services industry, I am eager to look into this program.
ReplyDeleteThanks for the links. Learning how to visualize data, or analyze large data sets (with R & Python) or learn a new language or code is mostly about spending time learning to read documents, working with others, and borrowing code (e.g., on github).
ReplyDeleteI enjoyed your talk on this topic. In the past couple of internships I had Tableau was used a lot throughout the company so it is kind of surprising we don't get some training on it throughout our normal coursework and something I would have liked to know more about. I like how easy Tableau is to use, I've basically described it to other people as an easy to use Excel that is more powerful. However, I have still found it has its limits when trying to analyze big data and I had to move over to Python or R after a certain point.
ReplyDeleteTableau can handle large data sets, but cleaning the data for input (or from excel) can be time-consuming, but R or Python are great, too. Will you use these in your future career? I think it depends on what you want to visualize.
DeleteThe masters students use Tableau in all their classes (learned it and practiced it). If you know how to visualization with large data sets, you will find this skill in particular what companies are looking for students with this skill. Cleaning data is probably a skill we should all learn how to do (before you can actually use any of these software programs). How to teach it during class... Any ideas?
ReplyDelete