First project presentation and me and my cohort colleague were tasked with presenting on the cleaning phase in tableau prep. This is a bit of a follow up on my previous blog.
Why?
It's necessary to clean data because in reality the data that you're tasked to work with will most likely be messy. As to what constitutes as 'messy', here is a mock data set we conjured up. We can see that there are fields (Weight, Price per pack, Quant per Q) that should be columns and misspellings of the locations. Also the client may ask for something, lets say revenue per quarter. This is essentially the understanding your data stage.
Now to know what the desired state of the data is, which can essentially shown below:
We now have the appropriate fields as columns now. Next is the logical transition; how we take our raw messy data, into the desired state we have above. The preppin' data blog has various techniques on cleaning, but for this specific data set it would be grouping (to correct misspellings) and calculated fields (to find the revenue per quarter).
Next step is to start building your workflow in tableau prep!
This a bit of quick and rushed blog, as I am now due to give the presentation to the rest of my cohort.