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The best way to understand how a data dictionary works is through a practical example. We’ll take an example of a database a commercial bank may use to store the data about its clients. This database may contain various attributes, such as the name of the client, address, phone number, age, gender, education, financial savings, loans, and many others. They’re each stored in a separate column.
In the data dictionary, the columns will be turned “sideways”, making them into rows in the data dictionary spreadsheet. The precise tables that the data dictionary is made of may depend on the DBMS (Database Management System). The data dictionary linchpin is the document that contains all the data dictionary tables (commonly named sys catalog). The names of the tables should be descriptive and precise enough to enable an easy guess of what each table may contain.
In our example, each attribute now occupies a row in a data dictionary spreadsheet. So, we have a row for each of the above-mentioned attributes. We’ll concentrate on one of them, for example, the hypothetical “client’s age”. It will have its own row with various columns providing elements that further describe this attribute. The first element will likely be the attribute name which is, logically, “client’s age”. The next element may provide the definition of the attribute – “age of clients” for example. The element describing the attribute format will simply be “number”.
As these entries will have the value of or higher, the data type element will be “integer’. Following this pattern, the data dictionary may include various other elements for “client’s age” and other attributes. It may include the element defining whether the attribute is required or not, possible values, maximum length or field size, the location where that specific data is stored, and numerous others.
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