Data dictionaries are documentation of your database metadata, such as the structure of tables and columns, relations and constraints. They help you understand what your data means to you, how it is used and who accesses it.
They help you build a better understanding of your data, which can prevent inconsistencies and conflicts during project implementation. They also make it easier to define responsibilities and enforce consistent use.
Using data dictionaries to define and document your database helps you create a consistent metadata language across the organization, which is a huge step toward improving business performance. Having the entire organization understand what each detail in your data means can lower dependencies, improve onboarding and increase productivity.
The dictionary is also an important tool for data stewards, who are responsible for maintaining and governing data inventories. Data stewards often have to deal with the challenges of defining and maintaining the data access regulations that govern their datasets, while also determining what the rights and responsibilities are for each individual piece of data in their inventory.
It can be difficult for teams to interpret the data they have access to, especially if they do not know what it means or what it does. This can lead to problems that could cost your company time, money, and credibility.
A data dictionary is a centralized collection of information about the content in your databases, which can be accessed by data management systems (DBMS). It can contain information about a database’s structure and the names, meanings, sources, and usage of its elements.
Some DBMSs have built-in data dictionaries, such as Oracle or Microsoft SQL Server. These dictionaries are a vital part of the data management process, as they provide information about the contents of your databases and their locations.
However, these dictionaries can be tedious to maintain. It can be a hassle to update the dictionaries with changes in your databases’ structures. It can also be a challenge to present and share these dictionaries.
In an Active Data Dictionary, the DBMS automatically updates the data dictionary with changes in your databases’ structures. It is an ideal solution if you want to consolidate your documentation with your changing databases without having to update it manually.
Another way to manage your database documentation is with a technical dictionnary, which can be created and maintained in a collaborative environment. These dictionaries can be written and edited in any language.
They can be structured into modules and visualized with Entity Relationship Diagrams (ERDs). This gives you a compact sharable overview of your database’s structure.
You can also create your own modules. To do so, navigate to the Modules & ERDs folder in your repository’s navigation pane and select Add module/ERD.
The most basic way to document a table is by giving it a meaningful name and a detailed description of its purpose. You can define these in the Title and Description fields. Some applications generate titles for you automatically, so it’s important to check this and ensure that the titles are accurate.