HCDE 210: Sprint 4 Process Blog
Jeff Pinkstaff
1) Exposure to Experience
My first experience with Tableau was confusing. I had downloaded what I thought was an excel file but when I tried to open the data as an excel file it kept telling my error. I was glad that I was working with other students in studio section because a friend quickly told me I should just open everything with “other” rather than specific file types.
Working in Tableau definitely had a learning curve for me. The major steps to figuring out the process were:
- understanding the measures
- understanding the dimensions
- Learning how to properly filter and drag properties to columns/rows
- Editing the dimensions and measures to show the right color/size/font to make a better visual.
What went well for me was figuring out how to do color. It wasn’t very hard at all I just never realized I had to drag the dimension from the sidebar into multiple locations multiple times to do it. What could have gone better for me would have been my graphical comparisons. I personally didn’t like my own dashboard that I turned in as much as I would have — had I spent more time on the project.
Unfortunate family circumstances sent me home for the weekend and Monday night was a night of group project work for another class so my only true time spent with Tableau was the evening the project was due. I think I could have figured out how to visibly show the Seattle U-district crime as a proportion of total Seattle crime had I had just a little more time.
2) Reflection
One major question I had while working with Tableau was how it figured out which criteria were “dimensions” and which criteria were considered “measures”. I was curious because I tried uploading a different data set to further explore and by looking at the excel spreadsheet it wasn’t always clear (or it didn’t always work — like with my Statistics class data set).
The major problem I encountered was the learning curve. I also wasn’t able to figure out how to create the graphs I wanted to make. If I were to do this differently I would spend more time exploring Tableau and watching tutorial videos while also hands on learning. My issue was that I didn’t really have the time over the weekend.
3) Wildcard
Question:
How can 911 data be used to stop future incidents?
Answer:
Using data analysis systems that large corporations like Amazon and Facebook use law enforcement could have the potential to stop future incidents. If they look closely at certain data groups like “auto theft” and “shoplifting” they could theoretically create a hot map of where these types of crime occur the most and then dispatch more police officers to that area for regular routine. They could also set up more security systems around public malls like University village if they have the exact locations of where the most things get stolen from. The data would just need to be properly collected and examined.
4) Another User Group
Two other user groups that could take advantage of this public data are companies and criminals. Companies that want to sell the idea of a “safe home” or “safe vehicle” to consumers could use the information to explain why a homeowner living in a high-theft area would want better security. Criminals might be able to utilize the data as well and see which areas the most theft occurs, which could indicate places that they could be more successful when it comes to robbery.
In my opinion the best use of this data would be by law enforcement to understand where they need to work the hardest to fix crime rates. That would probably have the greatest benefit towards society.
