Data Catalog vs Data Dictionary - Differences & Use Cases

In the modern age, companies are responsible for a mind-bogglingly huge amount of data. If you imagine as much data as possible, it wouldn’t even come close to the amount of data companies actually have.

This is because there are lots of benefits and opportunities that come with storing this much data:

• Improved decision-making: The more data you have, the better-informed decisions you can make
• Increased efficiency: By storing the data you need in one place, you can reduce your costs and streamline your processes
• New business opportunities: By analyzing large amounts of data you can identify potential opportunities, such as new products or services
• Improved customer service: You can use data about customers to identify their preferences, and pro-actively solve their issues
• What is a data catalog?
• What is a data dictionary?
• What are the key differences between a data catalog and a data dictionary?

But as Dolly Parton said, “If you want the rainbow, you gotta put up with the rain”. The rain, in this case, is worrying about things like security, privacy, governance, and compliance.

The more data you have, the harder it is to ensure and manage these things.

This is why things like data catalogs and data dictionaries are so vital. Not only do they help you get the most value out of your data, but they also help you to mitigate the risks.

In this article, we will answer these questions:

By the end, you’ll have a clear understanding of the two different concepts, why they’re different, and how both can benefit you and your company.

Data catalog

A data catalog is a tool that brings all your data sources into one place, making them all easily accessible and searchable.

Think of your data sources as local restaurants—your product database is Luigi’s Pizza, your sales CRM is Szechuan Palace, a SaaS integration is Biryani Hut, and Google Drive is Tacos El Rey.

Your data catalog is UberEats (or your preferred takeout service), bringing all those restaurants together, and making them available in one place.

And just like Uber Eats doesn’t need the restaurants to be in one place, a data catalog doesn’t need to move your data sources. It’s just giving you a view of everything, which can be used to analyze and make decisions.

(Is this analogy making anyone else hungry?)

There are several stages involved in building a data catalog, although different tools will carry them out in different ways:

• Active metadata crawling
• Profiling the data
• Lineage building
• Data relationships
• Classification

No matter what tool you use, though, the end goal is always the same—make it as easy as possible for people across your company to access, analyze, and get value from your data.

This is because doing so will result in a variety of pretty important benefits.

Reusability is one of the most important benefits. With a data catalog, you can reuse your data, getting even more value out of it. For example, you could use the data from one app to build a new app, create reports, or forecast for the future.

Data quality is another huge benefit of having a data catalog. By creating a central repository, and implementing validation rules, it’s much easier to find and fix poor-quality data and maintain a higher level of data quality.

Related: Best Practices for Improving Data Quality

Business leaders have to make decisions every day, but those decisions can only be as good as the data they’re based on. A data catalog gives you all the data in one place AND helps you to maintain a higher quality.

Meaning you and everyone in your business have a much clearer view of this data, so decisions can be reliably data-driven. This could be the difference between a good and bad decision, which could have huge ramifications on the future of the business.

Data dictionary

A data dictionary is a document (or set of documents) that contains key information about your data. This includes definitions and characteristics of data within a database or data source.

It’s a centralized resource, giving everyone in the company clear instructions on how to get the most out of the data. And by clearly outlining this information, it also helps to ensure the data remains consistent, accurate, and complete.

Here are some examples of the kind of information documented in a data dictionary:

• Element names
• Definitions
• Attributes
• Relationships
• Data owner
• Data usage info
• Data source
• Glossary

We’ve already touched upon a few, but there are a number of benefits that might not be as obvious.

For a start, you’re making sure that your company’s data is accurate, consistent, and complete. This is almost impossible to achieve without a data dictionary. And it’s instrumental is maintaining high data quality.

A data dictionary also helps to create a standardized view of data across your organization, which will both reduce errors and increase efficiency.

Staying on the theme of standardization, your data dictionary will also establish clear standards and rules company-wide, which is a cornerstone of data governance.

Related: Building an Effective Data Governance Framework

Main differences between Data Catalog and Data Dictionary

It’s probably quite clear from the above summaries, but data dictionary and data catalog are two very different concepts.

While a data dictionary provides information and guidance that will have a positive impact on the data, a data catalog has a much wider-reaching impact.

Essentially, a data dictionary contributes to the effectiveness of the data catalog. It’s a cog in the bigger machine.

But a data catalog brings not just all the data together, but also puts it in the hands of everyone in the company. It’s a hugely important part of data governance, data quality, and much more.

Related: Building a Business Glossary - Why and How

Conclusion

Both data catalogs and data dictionaries play an important role in managing your company’s data. But they play very different roles.

A data dictionary gives you a system for documenting the structure of a database, understanding the meaning of data elements, and identifying relationships between data elements.

Whereas a data catalog changes the way your company interacts and uses data by making it easy to discover and understand data, assess and improve data quality, and share data company-wide.

Want to see how to build a data dictionary and data catalog using OvalEdge? Schedule a customized demo with one of our experts.