Reference no: EM133621998

Discussion Post

Challenge: Business use case - Red30 Tech

- In the previous solution we mentioned a company called Red 30. As well as provisioning IT infrastructure for their clients, they like to share data with their clients about the services they're delivering. Red 30 already has a Tableau server that's used for internal use to monitor its platforms but they'd like to move away from the PDF reporting they currently generate for their clients towards a world where they can give clients access to a portal with everything the client needs in one place. Separate to this, they've recently been building up their data scientist team to help add value for their clients as a service. As such, they've developed a need to work with technology such as R and Python and they'd like to have these integrated with their Tableau server. Those are your requirements. This is a slightly more technical use case but we've covered much of what you'll need for these two separate requirements when we looked at the Enhancing Platform section. The main thing I'm looking for here is a high level explanation of what technologies from the platform will be used for. You don't need to explain how they work or worry about licensing. Over to you.

Solution: Business use case - Red30 Tech

- Okay, this solution has two elements, neither of which are directly related. Let's take the first one relating to the portal. A portal in most organizations aims to give people a single place to access and manage everything that makes up an application or a process. Red 30 is trying to build one to make their customer experience better. Part of that is having everything branded but also avoiding sending people off to other systems and needing them to log in multiple times every time they use different systems. Here, you can recommend Red 30 investigate an embedded solution with Tableau to solve this. The experience with Tableau service suggests they already have technical experience with Tableau, so they should have the skillset internally, and if not, they might be minded to make a strategic investment to hire for the skillset. One thing we didn't mention during the course is that when you have an embedded solution, it's usually best practice to have your external users, in this case, clients, on a separate instance of the Tableau server, and Tableau have a licensing mechanism to allow you to purchase what's called an embedded server. Think of this as a license for a Tableau server designed for external facing users. At present, Tableau Cloud doesn't have an equivalent, but I'm sure it's in the works, given the popularity of Tableau Cloud. The next requirement is a simpler one. To use \r\n Python, Red 30 will need to investigate features grouped under the analytical technologies. TabPy will enable them to run their Python libraries once their data science team is up and running, and they can also use R very easily with Tableau. The key piece of work is setting up the analytical extensions and making sure the workflow the data science team wants to use is tested with Tableau, so any work done by them can extend to works alongside Tableau. Again, that's a hugely simplified workflow, but given we only gave you a tour of the platform, that's all you really need to know to confidently talk about the options in the platform. Next up is the conclusion.

For this discussion, pick one of the three use cases that was discussed in Everybody's Introduction to Tableau and discuss

Question I. What were your learnings and findings in the use cases?
Question II. Did it change any previous notions you had or not?