Third day here at the Data School, and we have now taken our firsts steps towards the technical training. As mentioned in my previous blog at the end, we've now begun to dip ourselves into Tableau Prep. Before diving into the software itself, we had a session on the purpose of Tableau prep or what it does.
Often times data can be messy or from an initial perspective can be difficult to work with. This is where Tableau prep comes in clutch (also Alteryx, but that is uncharted territory from the time this blog was written). In a nutshell, Tableau Prep cleans, organizes, and reshapes data so that we can analyze it and communicate it more effectively.
Before diving straight in, it's best to just stop, think, and plan the steps for preppin' data. The steps or stages can be boiled down to the following:
Understanding the Data
Firstly, examine the data and how it is structured from the beginning. Ensure you have the required headers and fields you need as well as confirming the data types in them. Know and identify which data fields are categorical and which are values.
Desired State of the Data
You've examined the data and can confirm that you have what is required. Next is to think about what you want your data to look like, meaning you should know what outcomes you're looking for from examining the data set.
Logical Transition
Now that you know the desired state of the data, how are you going to achieve this? How are you going to clean the data? Perhaps you may need to filter out null values or clean and organize the header and field names or add some calculations based from the data.
Building
So you've examined the data, know your desired state of it, and thought about how to achieve it. Well, time to dive in now into Tableau prep (or Alteryx, still have yet to have a bias) and start your workflow to output some nice clean data.
With the end of our first technical training day, it is now time to look forward to tackling our first project and presentation.