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Home Data Science Data Science Tutorials Data Science Tutorial for Beginners Data Dictionary Tools
 

Data Dictionary Tools

Pooja Gupta
Article byPooja Gupta
EDUCBA
Reviewed byRavi Rathore

Updated February 2, 2023

Data Dictionary Tools

 

 

Introduction to Data Dictionary Tools

The data dictionary tools are the type of tools that are used to access the information stored in any repository and fetch the data from that repository. The data dictionary is a type of dictionary that compiles all the information related to data, meaning, relationships, the format of data, and usage of data. And by using these tools all the information can be gathered and can be used for fetching the information. These tools are also used for designing and building the data dictionaries. The data dictionary tool is mostly used for documentation of the database.

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Top 5 Data Dictionary Tools

The data dictionary tools are the type of tools that has a different type of metadata repository, it means it has separate GUI and other documentation tools. The main purpose of these tools is to design the documentation related to the database. These tools are rich in metadata capabilities that means it can be used to show the tables, relationships, a text editor is present, multiple types of descriptive fields. The tools are also rich in multiple databases and multiple engines that are present in one single repository. The tool has enough collaboration capabilities and the tool can be easily integrated with other applications.

In the below section some of the examples of dictionary tools are described below:

1. Dataedo

The Dataedo tool helps to document, understand, and catalog the data with the data dictionary, ERDs and business glossary. The tools provide the functionality to properly document the relational database and share the document in interactive type HTML. The document can be export in PDF< HTML or MS Excel format. The tool is not provided as open-source and users need to purchase commercial edition for use. The tool supports different types of operating systems like Windows and Mac OS.

2. Redgate SQL doc

This is another type of data monitoring tool that is used to generate the documentation for the SQL server and the documents are generated automatically. The tables used in these tools can be editable as the column, description, triggers, index, constraints can be easily edited in this tool. The database summary can also be generated by using this tool. The tool supports only the Windows operating system. This tool is also not provided as an open-source tool and users need to purchase commercial edition for use. The main feature of the tool is the automatic generation of documents and have the option to edit the object description. The documents can be export in HTML, CHM, PDF, and MS Word format.

3. Database Note Taker

This tool is an open-source tool that is easy to use and helps to share the knowledge and information about the database and also used to create the documentation of the database and data dictionary. The document generated in this tool provides quick access to the developers, support staff, and also the customers to access documents related to the database. The only format supported for the document is HTML and the metadata stored in the SQL server. The tool only supports Windows operating system.

4. Doc xPress

The Doc xPress is the type of data dictionary tool that is widely used for documentation of the SQL server database and for the BI tools. The tool also provides to edit the object descriptions and the document generation process can make customized as per the user requirements. By this only, the relevant information can be included in the document. The tool is not an open-source tool and is provided as a commercial edition for the user. The tool supports windows operating system only.

5. LeadumDBScribe

This tool is mostly used for generating the documentation related to the SQL database. The documents are generated automatically in this tool and the documents include complete technical information of the database schema. This tool is also not available as open-source and users need to purchase the commercial edition for using this tool. The tools support only the Windows operating system. The documents generated are highly professional and the templates used to create documents can be customized as per the user requirements.

Requirements to use Data Dictionary Tools

The only requirement for using the data dictionary tools is to first select the appropriate data dictionary tool as per the database used. There is a different type of data dictionary tool that varies according to the database used. And these tools are generated the documents that provide the information related to the database, objects, data, and relationship exist in the database. After the selection of tools, the next job is to purchase the tool as mostly tools are available as commercial edition and required to purchase. And after purchasing the tool, the tool needs to be installed and then can be used for generating the documents.

Advantages of Data Dictionary Tools

There are numerous types of advantages of data dictionary tools. Some of them are mentioned below:

  • These tools are used to form the database and fetch the information from the database. The quick report related to data stored in the data dictionary can be easily fetched using the tools.
  • The data management process becomes easy by using data management tools. As the data dictionary stores huge chunks of data, the tools help to ease the process and helps to manage the data.
  • The access management of objects stored in the data dictionary becomes an easy job. The authorized user can only access the data, view the database, tables. The unauthorized access can be control by the data dictionary tools. The tools have enough metadata capabilities that mean data relationship, text editor, and relationships all can be see using this tool.
  • In one metadata repository, there are multiple databases and also multiple engines in one single repository.

Conclusion

These types of tools are used for the design and documentation of the database. These are highly capable of generating the database documents automatically and the generated documents can be exported in different formats that include HTML< CSV, MS Excel, MS Word, and many more.

Recommended Articles

This is a guide to Data Dictionary Tools. Here we discuss the introduction Data Dictionary Tools along with top 5 tools and the requirements, advantages. You may also have a look at the following articles to learn more –

  1. Data Science Applications
  2. Data Science Lifecycle
  3. Data Science Machine Learning
  4. Data Science Tools

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