What is a Data Catalog? 5 Features of a Modern Data Catalog

Imagine going to a library in search of a specific book with a piece of information needed to finish an assignment. Did we mention you’re on a deadline? Good luck.

This scenario may seem extreme, but it’s the situation data consumers often find themselves in without a data catalog. In either scenario, you might have a general strategy — say, searching alphabetically — but how do you know which book or data point to pull without a summary? And how can you be sure there’s not another resource that’s more up-to-date or comprehensive?

Obviously, this isn’t a fast or efficient process, but it’s also not a very likely one thanks to technology. Just as libraries have book catalogs, enterprises with thousands of data assets increase speed and efficiency using data catalogs. So, what is a data catalog? Why do you need one? And most importantly, what capabilities are must-haves when deciding on a data catalog tool?

What is a data catalog?

A data catalog is an organized inventory of data assets that enables data consumers to locate, understand, and manage data in a centralized location. Data catalogs use metadata to allow data consumers – including AI agents – to quickly search their organization’s entire data landscape, understand the data available to them, and operationalize that data for insight-driving analyses.

Metadata is particularly powerful in serving up data that may not have initially been included in a data consumer’s search, but could be relevant to their purpose. This allows for deeper, more informed data analysis. For instance, a clinical trial analyst searching for data on a specific drug may query datasets labeled “Phase III results.” Metadata can link those results to other information, such as genomic profiles or real-world evidence registries, and surface relevant datasets in order to give the analyst more context and better overall outcomes.

Why do you need a data catalog?

Research from IBM shows business leaders spend 70% of their time finding data, and only 30% utilizing it. What good is your data if it’s only being used to a third of its potential?

The faster data moves – particularly in an age where everyone is a data consumer – the more businesses need processes in place that can keep up, both in speed and scale.

For example, if a company combines in-store shopper data, purchase history and cell phone data, they can serve a geo-targeted ad to a potential consumer at the point of purchase. The consumer is then more likely to buy that top-of-mind brand over a competitor that may be on the same shelf, but hasn’t delivered that time-sensitive nudge.

Data catalogs help you derive these insights, which can then inform digital ad purchasing decisions; so, in effect, the data catalog enables more efficient and effective ad buying that retrieves a higher ROI.

What’s the proof businesses benefit from data catalogs? In addition to improvements in efficiency, collaboration, data security, and general management, organizations that implemented a data catalog and management system saw:

• 57% higher profits
• 69% more revenue
• 72% greater customer satisfaction

What does a data catalog do?

According to Deloitte, organizations rely on an average of 28 different sources for data and metrics. Multiply those 28 sources by the thousands of data sets within each, and it’s easy to understand why businesses need a data catalog. By organizing data from multiple sources into a searchable, centralized platform, data catalogs enable users to locate, understand, and utilize data more quickly and efficiently.

How do they do this?

• Searchability: The ability to sift through a data catalog using keywords and/or filters, such as object name, source or date modified, makes locating the right data easier. Many data catalogs automatically sort by relevance or viewing frequency, so the best data is readily available.
• Analytics: Data catalogs connect with platforms like Redshift and Amazon EMR, which access datasets within the catalog to produce data analytics that can be inserted into BI tools for reporting.
• Unified management: Data catalogs eliminate silos by providing a centralized location to categorically house an organization’s entire data collection. This enables a self-service user experience and removes the burden on data stewards to grant access to data consumers on a case-by-case basis.
• Governed access: Integrating a data provisioning platform with a data catalog ensures data users can access governed data compliantly. So, although everyone can access the same data catalog, only data consumers with the right permissions will have access to certain data sets, thereby protecting sensitive data.

What are the limitations of a data catalog?

Data catalogs are evolving entities; the ability to curate data and manage it in a centralized location enriches the catalog and enhances the insights and results data teams are able to derive from it.

Still, data catalogs can vary greatly based on what they offer data consumers:

• Connectivity: Some data catalogs connect with a specific public cloud, while others have wide-ranging compatibility across clouds, databases and applications.
• Deployment: Data catalogs can be natively embedded within a data or analytics platform, or they can exist as standalone entities. Some standalone data catalogs are able to be embedded with an API for a more cohesive user experience.
• Audience: Data catalog users can vary drastically, ranging from an application that pulls metadata from the data catalog, to a data engineering or analyst team, to any number of AI agents that a company has deployed.

The variability of data catalog capabilities can make data governance teams’ jobs more challenging by creating silos that complicate data integration and operationalization. And, because data catalogs are used for finding data – not provisioning access – you still need a way to efficiently process access requests from users who have found the data they need.

Many teams – at least 30%, according to 400+ data professionals – still rely on manual, ticket-based systems to bridge the gap between discoverability and access. But this approach wasn’t built for the speed or scale that enterprises are now facing, particularly as AI adoption grows. And that’s causing burnout among the people responsible for making sure the assets found in data catalogs can actually be accessed and used.

The grow demand for data access is exposing this limitation of data catalogs – and forcing forward-looking teams to find new solutions.

What are the must-have capabilities of a data catalog?

Despite their limitations, data catalogs are foundational in modern data stacks. So, what should you prioritize when adopting one? Here are a few of our must-have capabilities:

1. Search and discovery: Searchability is one of the hallmark capabilities of data catalogs; it makes them self-service, enabling data democratization across your organization. Data discovery can also be achieved through tagging and filtering, allowing users to browse the data catalog using existing keywords or parameters.
2. Metadata curation: As organizations increasingly adopt hybrid data environments, in addition to traditional on-premises systems, a data catalog that can connect to and extract metadata from multiple databases, data warehouses, ETL, and BI tools, is key to scaling data access in a centralized catalog.
3. Automated data intelligence: Automated processes within data catalogs that incorporate machine learning and AI help avoid manual data tagging, classification, and organization. These technologies can also leverage data usage and queries to link or assign business context to data assets at scale.
4. Collaborative data use: An accessible data catalog allows even non-technical data consumers to locate and utilize data, enabling collaborative data use across an enterprise. Capabilities such as group projects and data annotation further this collaboration, which enhances user efficiency and data utility organization-wide.
5. Provisioning integration: We covered the need for a solution that provisions data access once users have identified the assets they need. Finding a data catalog that seamlessly integrates with a platform like Immuta to solve your last-mile data provisioning needs ensures that users get fast access to data, without sacrificing control or visibility.

Start putting a data catalog to work

Whether you’re just starting to search for the right catalog for your organization, or are looking to optimize your existing one, bridging the gap between data discovery and access is the best way to ensure that you maximize the ROI of your data catalog investment.

Hear from Immuta CEO and Co-founder Matt Carroll on how data catalogs integrate with data provisioning platforms in this short video: