The basic classification divides data dictionaries into two major categories – active and passive data dictionaries. Data dictionaries are not all the same as they may serve different purposes. Also, elements within a data dictionary can interact with users in different ways.
Active Data Dictionary
Active data dictionaries are built within database management systems (DBMS). They automatically reflect any change or modification within the host database. This means that if a user makes any change in the database, the change will automatically take place in the data dictionary, too. Most professional organisations have some sort of database management system, as it helps them avoid any potential discrepancy between the database structure and data dictionary.
Passive Data Dictionary
This type of data dictionary is a bit more complicated than the active ones and can take many forms. Simply said, this type of data dictionary doesn’t automatically update with every change in the host database. They’re built as new databases to store data dictionary information but are separate from the databases they are used to describe. They require more work to stay in sync with the host database and should be handled very carefully to avoid any potential discrepancies.
This type of data dictionary is most commonly created as a spreadsheet in programs such as excel. While these passive data dictionaries are not built to automate database-to-data dictionary encoding, the well-built and structured Excel spreadsheet can do this automatically. Other ways to create passive data dictionaries are by using data catalog tool Dataedo, data integration/extract transform load (ETL) metadata repositories, or data modelling tools.
Now, What is a Data Dictionary?
A data dictionary is a file or a set of files that contain information about objects in the database. It’s basically a repository of data names, definitions, and attributes used to describe the data. We can say its data about data. This is done by describing data columns based on common traits within another table.
The data dictionary may include information on data types, the meaning of data elements, allowable values, data ownership, security restriction, and details of the structure. These repositories containing metadata management software are crucial for maintaining the structure of an underlying database and communicating the information it contains. In addition, a data dictionary provides more useful information on relationships between different database tables, prevents data redundancy, and makes data well organised and easily searchable.
It allows users to understand even the most complex databases without the need to investigate every column. With a data dictionary, the business stakeholders’ requirements can be more easily communicated, so that technical personnel can design a database or data structure that answers those demands. Data dictionaries ensure that everyone in the organisation is on the same page when it comes to metrics and key definitions used in the company.