Chapters 6 and 7 taught me a lot of new things in terms of data mining and visualization. To begin, data visualization is putting a given set of data into a graph. They help to see patterns that are happening through different types of graphs such as; bar, line, bubble, and pie charts. The important part about data visualization is how you choose to express it, as said in the text "The challenge is to understand how the information visualization creates an argument and then make use of the graphical format whose features serve your purpose" (90). The key thing to note when it comes to rhetorical graphs is questioning the creator of the content as sometimes it can be deceptive. I also learned about networks and the complexion and how it "is that the development of the system cannot be predicted-- because the processes are nonlinear and/or non-deterministic from a statistical standpoint. Data Mining as defined in the book "is an automated analysis that looks for patt...
Comments
Post a Comment