'Learn What the Data School Learns' is a day of teaching clients a snapshot of what we have learnt whilst being part of The Data School. Oh how the tables have turned!
My hour and half session involved leading an intro to Tableau Prep. My biggest enjoyment of the day was showing everyone the value of clean, transformed data, with unique records and formatted fields. I think this part of data analysis can be overlooked, where pretty graphs and the final output attract priority. Hopefully I showed how much easier future life becomes when you have well-structured dataset to load in.
When planning the content for LWTDSL, I was overwhelmed with possibilities and directions that I could go in. I wanted to teach everyone to run before they could walk, so in fact, bringing those thoughts back and concentrating on the cleaning ability of Tableau Prep, was most useful. I noted some of the transformative abilities of Prep, including: joins, pivots, unions and aggregation, but we did not do any practical examples. In terms of content creation, I was lucky enough to have Preppin Data challenges that I could use and manipulate as content material, to solidify the skills I was teaching. Within data cleaning, the main skills I wanted to teach in Prep were the following:
- Cleaning spelling errors
- Parsing/splitting fields with too much info
- Changing the data type of a field
- Concatenating fields/ exposure to a calculated field
- Cleaning leading/ trailing space
- Promoting headers
- Filtering the data
The hardest part of the day was making sure everyone had Tableau Prep downloaded. In a way I think that’s a good thing, because at least the hardest thing wasn’t the content! However, in the moment I did need to adapt, so I pivoted by talking about the basics of what a clean dataset looks like and the theory of what we were about to do, whilst everyone was still trying to download.
Overall, the teaching experience went well; everyone in the room learnt something new, and it made me feel more confident about my own skills too.