Firstly, I was already familiar with all the topics covered in the data structures section because I had taken the Elementary Data Structures course. I also already knew about structured and unstructured data, spreadsheets, user interfaces, implementation, datasets, metadata, and databases, as those topics have been covered in various classes before. A term that I already knew about from outside sources (other than different courses) was personally identifiable information. Additionally, I already knew about investigating how social networking sites use your data, how it is collected, etc. I have personally read the privacy policies of various websites before, out of my own curiosity. However, like I have mentioned before, it is always useful to review and refresh your memory on topics, especially when they are a component of your degree or field.

The rest of the chapter was very vocabulary heavy and took me a while to fully understand. That said, I found the section on computational thinking was particularly interesting. I offered me a new perspective on how to break down and approach complex problems, which I found insightful. I will keep this in mind for my career, as I think it could be a useful strategy in the future. I tend to get overwhelmed sometimes when trying to solve issues. However, if I apply the approach of computational thinking, I feel it will be easier for me to digest the problem and work through it step by step.

I also think that learning various data terminology, such as the data aggregation and cleansing, will be helpful. I am not sure exactly what I will be working with in my job, so it is important to be prepared, especially when dealing with serious topics, like handling personal data. Knowing the correct terms and understanding how data works could make a significant difference in both protecting privacy and working efficiently.