Fall 2023 Semester: Databases!

     Based on what I learned in this class, it seems to me like a speadsheet is a fast and easy way to make calculations before putting it into a database, and a database is used to manage and display the data in different ways. At least that’s what it seems like from my own experience. The majority of my Excel experience involves inputting a bunch of data into the cells, and then using different mathematical formulas for calculations, and then displaying it in a table. For example, in one of my engineering classes at Glendale Community College, we used different formulas to calculate say, the distance of different projectiles shot out at different angles. It doesn’t seem like SQL allows that sort of thing. It seems like you could use Excel to make the calculations for your dataset, and then use SQL for management and to sort and display the data in the database.

For the group project, Jaira and I chose a CORGIS dataset with different cancer statistics for each state. It’s difficult to summarize this dataset both briefly and accurately. Despite the data being clean, it was very messy and confusing, and the information provided was not always consistent. But in a nutshell, this dataset shows cancer statistics for 51 states. It includes total rates, as well as rates for age groups, race, sex, or a combination of these. In addition, it also shows total rates for three different types of cancer (breast, colorectal, lung) as well as statistics for age, race and sex for each of these cancer types.

After picking our dataset, we started out by creating an ER diagram for the data. This was rather challenging, especially with the plethora of information our dataset had. I was pleased to find out that my guess for the ER diagram were not totally off, but we definitely needed quite a lot of assistance. Dr. D even realized later on that we needed a fourth table!

Using SQL, we wrote export queries and created our tables. We had to use insert statements for two of the tables to input the data how we wanted. We also used constants for our export statements. This made it so that each individual value had its own row in our table. Our finished table had 3,612 rows!

Afterwards, we each made our own queries so we could select and order specific information from the table.

    I definitely learned a lot about SQL and databases from this project, even a few things I didn’t learn to do in my actual database class. We got to pick a data set and learn how to create an ER diagram from scratch based on the dataset, which is something I hadn’t even done in my main database class. We used SQLite for the database and queries. We learned how to import a .csv file to it, export information from the dataset, and used that information to create our own database using the information. I also learned how to create constants in SQL to assist in displaying the data how I wanted it to be displayed in my database, which is also something I did not learn to do in my database class.

    I was interested in getting into database stuff for a career before I learned about databases, partly because I was interested in AI and machine learning. This class and my regular database class have definitely reinforced this plan. I also have a fairly decent background in biology, and I’d like to work with biological data. I will say, I was so tempted to ask if Jaira and I could pick an easier dataset for our project. The time and stress of handling a complicated dataset as beginners felt pretty overwhelming after it hit me that I was completely lost on what to do, especially because I also needed to further teach Jaira about SQL. However, I honestly really enjoyed it and I’m glad we had a confusing dataset because I learned a lot more because of it. Also, if I work with databases for my career, they are not going to be pretty. Also, teaching someone else about a subject is an incredibly great way to reinforce knowledge on a subject, and also made me realize what knowledge I need to learn more about. 
I was probably not the greatest SQL teacher, because as I was explaining something to Jaira, I was making my own learning connections as I went. It was great for me! But not so great for her, because I would be like "... wait, actually..." And it definitely made it more confusing for her.