phpMyAdmin exploration:
I was able to locate phpMyAdmin with little difficulty, but once there I was at a bit of a loss as to what to do. I clicked through the tabs – Browse, Structure, SQL, Search, etc. – but nothing jumped out at me as something to do. I have no real idea what SQL is, and everything looked a bit like techno-gibberish. I clicked around the file system on the left sidebar, but only to identify the folders from your WordPress database model. When I went to enter data, I only got errors saying:
“#1064 – You have an error in your SQL syntax; check the manual that corresponds to your MariaDB server version for the right syntax to use near ‘2,3,4,5) NOT NULL, `name` INT(2,2,3,3,3) NOT NULL) ENGINE = MyISAM’ at line 1”
I was also unable to import CSV files that I’ve analyzed in the past because of some reason I’m not quite sure of. Another incomprehensible error.
I met with more success when trying to install a new plugin and theme. For the plugin, I chose one which will enable sharing of my posts on social media sites like Facebook and Twitter. It was very easy, and the specific plugin that I used was MashShare.
I ended up choosing a theme called Gray Chalk, made by Busy Momi Bee because I liked it. It also was formatted in such a way that I didn’t have to re-add a header link to my About Me page, which would have been the case for some of the other themes.
Database Analysis:
Prior to this assignment, I had never really given much thought to how data was stored. I’ve taken a good number of courses that require me to work with datasets – Stats 215, Econometrics, Applied Regression Analysis – but what I’ve always uploaded into my statistical analysis software has always been a CSV file (comma separated values), which is a flat database. Now that the question is posed to me, I can certainly see some of the pros and cons of using both styles of database.
Pros of flat:
- Simple. For smaller datasets, creating a flat database will take less effort than creating a relational one, with minimal drawbacks.
- Accessible. Conceptually, a flat database makes sense to anyone, and can easily be drawn on paper.
Cons of flat:
- Inefficient for large datasets. Both with respect to separating and viewing your data, a massive dataset is very difficult to work with and manipulate with too many observations or parameters.
- So oldschool. People have been using flat databases for thousands of years. Get with the program, people
Pros of relational:
- Flexible. Because a relational database is inherently separated into many different pieces, data manipulation is very easy.
- Efficient. Because of its nature, there is less storage of redundant information overall, resulting in a smaller file size than a corresponding flat database.
Cons of relational:
- Inefficient for smaller datasets. While the flexibility of relational databases is useful, a dataset with not many observations or parameters would be easier to create and just as useful.
- Complicated. The concept of a relational database takes some explaining, automatically making it harder to use than a flat database.
These pros and cons are somewhat simplified, but I don’t think blog posts are the place to delve deep into the technical differences between the two data storage styles.
