Top 6 Data Dictionary Tools To Discover Data

Is your data team struggling with data discovery? Or, keeping up with an increasing number of datasets taking too much time and causing work-bandwidth issues? And probability dictates that if you are a data folk, you would be scratching your head over these questions:

• Is this the best data resource that can help find the solution?
• How trustworthy is this data resource?
• What does the column name ‘YYYY’ mean?
• Is this database updated? And, which process created this data?

If yes, data dictionary tools can help you spend more time on value-adding work, diverge from lackluster traditional processes requiring scavenging through data manually. In this article, we will spotlight the need for data dictionary tools. And provide a list of the top 5 data dictionary tools that might change how you process data in your organization. Let’s begin.

Understanding Data Dictionary and Tools

Data dictionary, referred to as meta-data, is a repository of data about data.

Metadata is information about each dataset or schema, such as a table, event file, or column. For example, the metadata related to the specific laptop you are using includes the model number, manufacturing details, compliance ID, and so on. Through these extended details — metadata — one can easily navigate through different laptop models and locate similar to yours in no time. 

In general, a database table looks like this:

Name	Email	Employee ID	Gender
Monika	monika@yahoo.com	1100	F
Ross	ross@gmail.com	1101	M
Ted	ted@gmail.com	1102	M

And, its metadata looks like this:

Column Name	Definition	Data type	Required
Name	This column refers to the first name of the employee	String	Yes
Email	This column refers to the personal email ID of the employees	Varchar	Yes
Employee ID	This column refers to the unique ID that is given to every employee in the company	Numeric	Yes
Gender	This column refers to the gender of the employee	String	No

Why Data Dictionary Tools are Important?

Data dictionary tools are of immense use to collect, organize, and manage data. Some of the reasons why they are so useful are:

• Data Accuracy: They ensure data integrity by standardizing it. This makes your data reliable, accurate, and of better quality.
• Data management: It makes it easier for your teams to traverse and identify patterns in data. 
• Consolidates data insights: By enabling quick access to data, data dictionary tools help get better data insights.

A tidy-looking workplace begets better workflow processes. And, it is also true in the case of data folks because locating and structuring data is as crucial as analyzing. But, due to information silos, it’s hard to get a holistic overview of all the operations data, creating confusion around data definitions which creates bottlenecks in business processes, leading to operational barriers or inaccurate data analysis.

One solution might be to develop a data dictionary or search for 3rd party data dictionary tools that can create a data dictionary for your data team to better understand what data implies.

Key Components of Data Dictionary Tools:

Some key components of effective data dictionary tools are:

• Data Organization and Management: Through its features like data catalogs and metadata management, data dictionary tools organize and manage data. It divides data logically into specific categories and provides comprehensive information about the same. 
• Collaboration: They enable the sharing and collaboration of data. It also facilitates tracking of any changes in data and better usage analytics which helps you to know what changes your data has undergone. 
• Database Interaction: It is the most essential component of data dictionary tools, capable of connecting to databases and extracting data from them, which can be used to get better analytical insights. 
• Technical Functions: Data dictionary tools should customize the interface and should integrate with other data analysis tools. They should also be compatible with different operating systems, such as Linux or Windows.

Choosing the Right Data Dictionary Tool

 You can choose a data dictionary tool as per your needs by keeping in mind the following things:

• Requirements: You should keep in mind what you want to use the data dictionary software. Become aware of its features by researching and consulting with your data team. 
• Compare the Tools: You can compare various dictionary tools available by comparing their features, such as security, scalability, functionality, etc. This will help you get a clear idea of what tool you want to use for your business. 
• Cost Comparison: Along with features, compare the costs of the tools so as to know which ones are suitable as per your budget. 

Trials: You can try out different free data dictionary tools before finalizing any of them. There are many open source data dictionary tools that have the facility of free trials, which you can use to know what you need.

Top 5 Data Dictionary tools

In the section below we have talked about some of the best data dictionary tools and their advantages. These are the best performing tools in the market that can help you create data dictionaries for better data discovery.

Dataedo

Dataedo is one of the most popular data dictionary tools. It was anointed in the 2020 Gartner Peer Insights Customers’ Choice for its metadata management solution. The software enables users to navigate through millions of documents and share data in HTML format. Dataedo helps find meaning to data by adding information to datasets that you are familiar with.

Here’s what we liked about Dataedo the most:

• It’s easy to locate data with Dataedo: Users can add connections between datasets and tables to grant the reader a better understanding of data.
• Organized data means seamless business processes: With different teams and departments holding onto different sets of data, it becomes imperative to organize data accordingly. Dataedo helps you manage the complexities of business operations by allowing users to create segmented data profiles for each department/team to help organize large sets of data.

Redgate SQL Doc

Redgate helps IT teams balance the need for delivering software products faster while protecting and preserving critical business data. Redgate SQL Doc is an excellent tool to document data automatically and create a detailed data dictionary from within SQL Server Management Studio. The software automates database reporting in HTML, PDF, Microsoft Word, or Markdown formats. Users can easily edit descriptions for columns, indexes, triggers, and constraints for tables and views using the software. 

Here’s what we like about Redgate the most: 

• It automates the process to create lean data dictionaries: Redgate automatically updates data with the latest definitions and cross databases relationship. The process reduces the time spent on data documentation tasks, helping developers to focus on value-adding tasks.
• A robust solution to seamless DevOps: With Redgate’s advanced features, enjoy a whole suite of data management tasks like standardizing team-based development, database development and deployments, data security, and compliance reporting. In short, Redgate helps today’s DevOps deliver updates and new software faster.

Database Note Taker

Database Note Taker is an open-source tool. It is easy to use, provides an intuitive platform solution to the data dictionary and documentation needs. Database Note Taker offers relevant databases for developers and concerned staff — in only HTML format — with the metadata stored in the SQL server. But, the tool only supports Windows operating system.

Here’s what we like about Database Note Taker:

• It’s a simple, focused tool: Database Note Taker only serves information in HTML format, hence, making it an attractive solution for non-technical users. Also, the best part is that the software shows the users if the data objects have a data dictionary created for them or not.
• Developer friendliness: While developing new databases, developers might make new database relation copies; this does not interfere with the actual project files, so they remain excluded from the real data dictionary. Moreover, database Notetaker is not limited to a particular database platform, making it an agile tool for developers working in different coding environments.

ApexSQL Doc 

ApexSQL Doc tool is a data dictionary tool that enables users to create data dictionaries of SQL server databases. It automates the creation of the SQL database documentation. And, using the software, users can share files in CHM, HTML, Word, MD, and PDF format. AexSQL features a suite of offerings that can help increase data teams’ productivity. Learn more about ApexSQL Fundamentals Toolkit.

Here’s what we like about ApexSQL Doc the most:

• It’s a powerful data dictionary tool: ApexSQL Doc has multiple documentation formats, which can produce documentation in CHM, HTML, DOC, DOCX, MARKDOWN, and PDF format. Additionally, the added functionality allows users to create documentation in SSAS, SSIS, and SSRS database format.
• It helps minimize data inconsistency: Data inconsistency happens when different versions of the same data appear in other places. ApexSQL’s properly designed database reduces the probability of data inconsistency issues significantly.

dbdesc

dbdesc generates a data dictionary describing your databases. The relationships between databases are generated automatically with complete technical information about the database schema. The software includes a built-in SQL server that helps you annotate databases. Dbdesc’s main features include table dependency matrix, wizard-based interface, extensive database info extraction, syntax highlighting, and much more.

Here’s what we like about dbdesc the most:

• It improves data sharing: dbdesc takes advantage of the database management approach to create data dictionaries to look into better-managed data.
• It offers impeccable data security: dbdesc is compliant with major data security policies; hence the risk of a data security breach is close to none. Moreover, a DBMS approach provides a network security framework to enforce better data privacy, security, and governance policies.

Alation

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Its data cataloging and collaboration tools enable you to understand your datasets better. Their central repository helps you to share and collaborate your data with others. It also has features that are useful for data governance, quality management, and lineage tracking. 

Here’s what we like about Alation the most:

• Improved security and accessibility with cloud data migration
• Centralized reference for all data
• Self-service analysis and data governance tools

Conclusion

Through an organizational lens, data dictionaries are used to create data standards to govern the way employees collect, record, and present data. The way data is stored and defined can have positive and negative cascading effects for your organization because good data collection begets good analytical insights. So, it is safe to say, good data dictionary tools can help increase the usability of data, and ensure data is recognized beyond immediate analytical need.

Once the need for good data collection has been established, the need for good data analytics becomes paramount. And, to ensure data analytics, secured data pipelines are a prerequisite — and, Hevo can help!

Hevo Data is a no-code data pipeline platform that helps new-age businesses integrate their data from multiple sources systems to a data warehouse and plug this unified data into any BI tool or Business Application. The platform provides 150+ ready-to-use integrations with a range of data sources and is trusted by hundreds of data-driven organizations from 30+ countries.

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