It is about time for another update for my capstone project. Last time I discussed our roadblocks with being unable to get all the data we need. That roadblock still remains. We have some data, just not all the data we need to start an analysis.
Luckily, this time we decided to be a lot more proactive and strengthen our skills in data analysis. For our first testing, we decided to use Malloy to analyze real estate data. Malloy, as mentioned earlier, is a data analysis programming language similar to SQL, but intended to be more efficient. Using Malloy, we each came up with our own analysis on the data based on the tables that were formed from the output of our code. For example, Brayden found a positive correlation the number of convenience stores in an area and the house price per unit in that same area.
Our second test is currently in progress. We are testing sentiment analysis, which will be useful for rider satisfaction analysis for LTD. We are using Spotify reviews, but we can apply this same logic to our transportation reviews. Something we picked up on is this data is especially useful for someone who understands the domain. For example, a sentiment analysis on Spotify reviews would be particularly useful to someone who works at Spotify. Working on this was also able to get us comfortable with using AI API’s to conduct the sentiment analysis.
Overall, I would say progress is being made without progress actually being made. We are staying productive and doing what we can with what we have. When the data comes in, we will have a lot more to discuss and hopefully have some very interesting things to share.
