Data Science

by John D. Kelleher

A milestone in data collection and storage occurred in 1970 when Edgar F. Codd published a paper explaining the relational data model, which was revolutionary in terms of setting out how data were (at the time) stored, indexed, and retrieved from databases. The relational data model enabled users to extract data from a database using simple queries that defined what data the user wanted without requiring the user to worry about the underlying structure of the data or where they were physically stored. Codd’s paper provided the foundation for modern databases and the development of structured query language (SQL), an international standard for defining database queries. Relational databases store data in tables with a structure of one row per instance and one column per attribute. This structure is ideal for storing data because it can be decomposed into natural attributes. Databases are the natural technology to use for storing and retrieving structured transactional or operational data (i.e., the type of data generated by a company’s day-to-day operations). However, as companies have become larger and more automated, the amount and variety of data generated by different parts of these companies have dramatically increased. In the 1990s, companies realized that although they were accumulating tremendous amounts of data, they were repeatedly running into difficulties in analyzing those data. Part of the problem was that the data were often stored in numerous separate databa...