The exploration of my website’s back end did not go as well as expected, since even opening up the phpMyAdmin site was overwhelming and puzzling in all the information it seemed to offer. At most I figured out how to edit the site in the same ways I can directly through the WordPress interface, but moving into other tabs of the php I found I couldn’t understand how to properly make us of the prompts and information provided there. After exposure to the database conundrum, I figured the use of a relational database seemed to be redundant and in most cases pointless, since the main point was apparently to reestablish groupings created in the flat one. After some consideration, I see how a relational database could be more useful to condense what would otherwise be an expansive data set.
As for pros and cons, Flat Databases are useful in their presentation, providing immediate access to all data points, and thus a manageable way to compare them. Sorting flat data sets is also easier than a relational database, as one does not have to worry about the shifting of related values in other graphs. The layout is consistent, so even if you have a large pool of y(?)-values, the reference point to the column headings is the same. Similarly, they are fairly easy to set up and populate, but are most ideal for smaller data sets, which leads into the cons.
Flat databases have no way of representing complex relationships between points, in other words they can only display the connection between pieces of information provided in the rows/columns. Furthermore these points cannot be easily indexed. Conversely, when working with larger sets, a flat database is too spread out and obfuscating.
Relational Databases, on the other hand, are optimal for large data sets with similar genres of information. The ability to combine different subsets into graphs provides a flexibility when attempting to change or index entire sets. This form is also more efficient (space-wise) than flat databases when dealing with large sets.
Negatively, relational databases are, in essence, subjective to the author’s understanding of the relationship between different groups of the data. Even if working with the same data set, separate authors might come up with different subgraphs, which causes a problem when attempting to combine similar data from separate sources.
Before choosing either, it is important to take into account the influence of data collectors on the data and how that might manifest in the separation of data points into groups.