Hey AJ! Similar assignment to last time - Are you able to assist?
Context: Conduct an exploratory data analysis on data from the Department of Buildings in New York City. For every meaningful change to a building in NYC, an application has to be filed to the DOB. The DOB has to approve the change and often gets some revenue as a result of the application. The commissioner of the DOB is interested in many things and you should use your best business judgment around what they would find interesting. Touch on:
Are we making more revenue this month than we did last month (this is from the Total Est. Fee column)?
Is the DOB making at least $200,000 a month in fees?
How much revenue did we make this month? How is that different across Individuals, Corporations, and Partnerships, and Other categories (where Other is none of those)?
What is our average time from the filing date to the application being assigned?
What is the average time from the assigned date to being fully permitted?
Where are the projects that take more than a month to go from Filed to Fully Permitted?
How many applications do we have related to "Solar Panels" each month?
- How many projects have not yet been assigned or fully permitted?
- Key Tasks
- While working on your visualizations, use the linked data
- The data starts on January 1st, 2020 and goes through 1/3/2023. You should pretend that today is 1/3/2023 so that your date filters look normal.
- Be careful about the Job # column - remember that is a randomly assigned number to each application, so if you sum it you're going to get nonsense (and lose lots of points - summing the Job # column is possibly the biggest mistake you can make on this dataset).
- In the second tab, there is a data dictionary you can refer to. You should not visualize or import the Data Dictionary in Tableau - it simply doesn't make sense to visualize a data dictionary.