Join Ben Sullins for an in-depth discussion in this video Tableau desktop overview, part of Integrating Tableau and R for Data Science.
- [Instructor] Now let's take a look at Tableau Desktop, and try to understand it a little bit better. So Tableau Desktop is the core product of Tableau that can import and enhance data, and it allows you to visually explore it and then publish it out online for collaboration. And the way it works is, first we have our data sources, and Tableau Desktop can connect to almost any data source you have including flat files, like CSV files, R data files, databases like SQL server, and cloud sources like Salesforce and Google Analytics, so it really aims to please here and work with any type of data that you may come across, and in fact, even letting you combine multiple types of data in the same workbook to analyze them together.
And when you connect, you can either do a live connection, where the data is real time and queried every time you make a change, or you can extract it, creating an offline copy to work from. The extracts are often faster, but can become a bit unwieldy in size if your data source is extremely large, so tread lightly there. Now once you have the data in Tableau Desktop, this is where you actually perform your analysis, and when you're ready, you can share that with your consumers. You can send them a static file, like a PDF, or a Tableau workbook that they can actually browse around and see.
Now this is a bit dangerous because now you have sensitive information floating around. Now with Tableau server, you get all the enterprise features that your IT team probably craves for, and for this to be a viable option, this is really what you need to be thinking about if you want it to be an enterprise solution. So with Tableau server, you have data governance settings, methods of collaborating and distributing via the web, so no files being emailed around with sensitive data or anything like that, and no more outdated versions.
The version on Tableau server should always be the latest version. Now along with those things, you can get a decent set of security protocols including single sign-on, so if your company already has its own corporate intranet with sign-on mechanisms, you can integrate those with Tableau server so that way it's secure, and it's not adding to the confusion of passwords (chuckles), and stuff you have to keep track of, it just integrates directly with the rest of your corporate infrastructure, and it also can do things like automate common tasks, such as updating your extracts.
So if you extracted data from SQL server let's say, and then shared that to your Tableau Server, you can have Tableau Server go automate that, and pull that data in again and again, so you don't have to update the extract any time you want to, and you can set it up on a schedule even. So from there, your users can consume these visualizations directly in their browser, or through a set of mobile apps, and sometimes even, if you allow them to, interface with it in a way that allows them to edit it. They can create calculations. They can modify the visualization.
They can save their own version from their tablet or phone. So this is really the enterprise solution here. Now all of this works with R, and you can run R locally when you're testing, and then you need to run R on the server, and we'll get into that a little bit later.
- Where Tableau shines
- When R is the best option
- Installing Tableau, R, and Rserve
- Running Rserve and connecting Tableau
- Basic scripting in R
- Importing data to Tableau
- Linear regression
- Setting up R on Tableau Server
- Publishing your work
- Editing calculations