It’s becoming increasingly common for data experts to advise that the first building block in your data stack, the first tool you invest in, should be a data catalog. But what exactly is a data catalog? What does it do? And how is it different from a data dictionary?
Here, we’ll define both a data dictionary and a data catalog, explain exactly what each can do, and then highlight the differences between them.
What is a data dictionary?
A data dictionary provides information about your data in the form of detailed definitions and descriptions of data, and related information including attributes, fields, or other properties. It’s a technical and thorough documentation of your data and its metadata, serving as a repository for information on the type of data you have and everything related to it. It explains the definition and meaning of all columns in a data table and helps catalog the structure and content of data at the column level.
A data dictionary is useful for technical data people, as the information it contains helps translate business terms into technical requirements, allowing IT teams to design a relational database or data structure that meets business requirements for data management.
Data dictionaries are a crucial tool for metadata management and managing data quality within data warehouses or a data lake, and they are often presented in spreadsheet format with rows and columns defining each attribute or metadata category that needs to be addressed in a system.
What is a data catalog?
A data dictionary is an integral part of a data catalog. And while a data dictionary provides technical information about your physical data assets, a data catalog is a tool for self-service data search and data discovery.
According to Gartner, a data catalog, “...maintains an inventory of data assets through the discovery, description, and organization of datasets. The catalog provides context to enable data analysts, data scientists, data stewards, and other data consumers to find and understand a relevant dataset for the purpose of extracting business value.”
A traditional data catalog is a complete list of your data along with search functionality that allows your business users to find what they’re looking for, plus some additional information about the data (technical metadata and business metadata) that provides technical and business context to let them know what it is.
Data catalog use cases
Data catalog use cases can include:
Enable data discovery and provide context for data analysts and business users
A data catalog tool empowers data consumers the means to find, understand — via business context — contribute to, and work with data assets.
Unify all data platforms and sources
It’s rare for an organization to have all its data assets stored and managed in a single location. Data scattered like this throughout a company can lead to siloed data and team disconnection. A centralized data catalog tool lets anyone in your org find what they need regardless of where it’s stored, breaking down silos and improving enterprise-wide discoverability.
Org-wide collaboration
A data catalog allows you to bring together data producers and consumers in real-time, eliminating knowledge gaps, and capture ideas, questions, and results in context so you don’t have to slow down to stay in sync.
Speed metadata management for technical users
Data catalogs equipped with machine learning can simplify, accelerate, and even automate metadata management, eliminating busy work so your technical teams and data engineers can focus on higher ROI initiatives.
Facilitate data governance for compliance managers
Compliance managers and data owners can implement data governance policies within the data catalog, tagging sensitive data and establishing data access control and privacy.
An example data catalog and its benefits - ours
At data.world, our enterprise data catalog is all of this and more. Yes, data.world is a one-stop data and metadata repository, a data dictionary, business glossary, and a discovery engine, but we’re proud that our next-generation, knowledge-graph-powered data catalog provides even greater benefits beyond those of traditional offerings.
Our catalog makes data discovery a breeze — courtesy of a self-service interface that puts data in the hands of users; semantic intelligence that highlights relevant concepts beyond exact search; and multi-source integration that connects all your tools and data sources to create a one-stop shop for all your data and metadata assets; this cataloging of all your metadata across the complete data lifecycle is what makes search and retrieval of your data possible.
Another of its use cases: It can help your organization establish a data governance system that gets the right data to the right people, provides them with the tools to access and understand it, ensures regulatory compliance in terms of data storage and use, and allows stakeholder collaboration in real time to add knowledge and context to drive maximum business value.
Beyond that, data.world’s data catalog empowers data users to trace the history of your organization’s data — where it comes from and how it changes along the way — via an enhanced graph visualization that enriches your metadata and data lineage experiences.
There’s much, much more that differentiates our data catalog from the competition. Learn what else sets us apart here.
