3.1 Introduction<\/p>\n
Consider the data in Table 3.1 for a course enrollment system.<\/p>\n
The data in this table is essentially a flat file. Though we\u2019ve presented it in a nicely formatted table, this data is essentially no different from a Comma-Separated Value (CSV)<\/a> file in which each line represents a record and individual column values are delimited with a comma. The same data as a CSV file is presented in Figure 3.1. Flat file representations of data are called such because they take related pieces of data, such as which courses a student is enrolled, and flatten them into a single table representation. Even ancillary data that have a completely different relationship (such as emails) is included in the \u201cflattened\u201d representation.<\/p>\n Flat file representations can lead to a lot of problems, limitations and can lead to data anomalies. To motivate the use of a proper database system, we identify several of these here.<\/p>\n The solution to (most) of these problems is to use a proper Relational Database Management System (RDMS). A relational database stores data in tables. Tables delineate data in columns and rows. Each column holds a specific type of data (integers, strings, etc.) that define fields of records. Each row in a table corresponds to a single record.<\/p>\n","protected":false},"excerpt":{"rendered":"\n