Representing data electronically very often involves the use of some kind of table or tables. However, whether to use only one “flat” table or a number of tables in a larger relational database is a major question for every data representation project. Stephen Ramsey describes this relationship in his article on databases.

Flat tables like spreadsheets and CSV files are very advantageous in terms of ease of use and space consumption. They are very useful for fewer categories of items and simple data analysis. However, security is not great on these types of files and editing these tables can be annoyingly complicated depending on what type of flat table is being used.

Relational databases, often made using SQL (Structured Query Language) perform much better when there is a large amount of data with variables that have multiple connections between other variables. They allow for easier searching based on various characteristics, which is important when there is so much data. Databases can be confusing at times, and they tend to take up much more space, so in terms of simplicity they are generally pretty rough.

In general, both flat tables and relational databases are very good options for storing data, but choosing the right one for your dataset is key to making a project manageable.