20+ Key Features of Data Catalogs To Pay Attention To This Year

Data catalogs are amazing tools for data search and discovery. Discover the must-have features your data catalog should have and more here.
Last updated
May 2, 2024

Data catalogs are amazing tools for data search and discovery. The demand for comprehensive data catalogs has grown in recent years, and there are a lot of options available on the market today. However, not every data catalog may have everything you need. In this blog, we’ll go over the top 20 must-have features your data catalog should have in 2024. Read on to learn more, or get started with Secoda today to see if our data catalog meets your organization's needs.

Ability to consolidate your data tools

It's not enough to only have a data catalog anymore. Data teams are being asked to do more with less, so you should ask the same of your tooling. Being able to consolidate your tools will let you be more efficient with your budget. Data catalogs need to have lineage, documentation, as well as monitoring and observability functionality. This reduces complexity in your stack and saves money.

Infrastructure cost management

Being able to set thresholds and reliably scale your team's compute costs is a function that should be enabled through your data catalog. Data quality as well as metadata monitoring is an essential feature in evaluating a catalog for your modern data stack as cost management grows as a priority for data teams.

Native Integration Connectors

Native integration connectors are a must-have feature because they allow you to seamlessly get your data catalog seamlessly integrated with your data platforms and data sources. These out-of-the-box connectors allow you to skip the arduous process of developing APIs to connect the databases, data warehouses, data lakes and all other data-related tools you use most. It saves time and effort while also ensuring that there aren’t any obstacles to integration.

Customizable Data Browsing and Filtering

Another key feature to keep in mind is customizable data browsing and filtering. This allows users to find the data they need faster. They can tailor searches to filter by data types, attributes and other metrics to find specific data for analysis and reports. With a personalized data exploration process, your team members will have the flexibility to improve data-driven insights while also maximizing productivity.

Data Governance

Modern data catalogs should include features to help you improve data governance. Data governance features make it easier to enforce policies, stay compliant with industry regulations and improve data quality overall. Access management controls and automated data lineage are some tools that your data catalog may include to help you improve your data governance and mitigate your risk of noncompliance penalties and fines.

Active Data Lineage

Your data catalog should offer end-to-end active data lineage. This means that your data catalog should allow you to track data from its origin to its destination, showing you any changes or transformations it made along the way. Being able to view your entire data pipeline not only helps with your data governance but it helps you to spot downstream errors and improve data quality overall. Ultimately, active data lineage increases trust in data, reduces time spent on troubleshooting and enables faster decision-making.

Column-Level Lineage

Column-level lineage is also an important data lineage feature your data catalog should have. This more granular view of data lineage makes it easier to conduct root cause analysis and identify data errors at their source. Column-level lineage allows you to look at a data set from ingestion to visualization, so you can see every change made when running impact analyses.

Active Metadata Management

Active metadata management is an essential feature for robust data catalogs, allowing your team to track the usage and consistency of metadata across your organization. Active metadata management allows data stewards to access and analyze metadata across data sources and data tools. This improves data-driven decision-making by making it more efficient to access business insights. Data catalogs with this feature can also help maintain a healthy metadata environment by reducing errors and inaccuracies.

Advanced Search Capabilities

Modern data catalogs should include advanced search capabilities that allow any user to explore and discover data insights. Advancements like natural language processing empower even nontechnical users to access the data they need when they need it. In short, enabling better data search allows for more efficient and effective data discovery, helping to boost productivity and reduce data request bottlenecks for the data team.

API Extensibility

API extensibility is a crucial feature to consider when choosing a data catalog in 2024. With API extensibility, organizations can seamlessly integrate their data catalog with other applications and systems, allowing for easy data sharing and collaboration. This feature also enables developers to extend the functionality of the catalog by building custom applications and integrating them with existing tools. Whether it's integrating with analytics platforms or creating custom workflows, API extensibility empowers organizations to leverage their data catalog to its fullest potential.

Data Lineage Visualization

We’ve talked about the importance of data lineage, but it’s also important to consider data lineage visualization capabilities when choosing a data catalog. Data lineage visualizations will allow your team members to generate clear representations of the journey data takes in your organization. This makes it easier to identify issues and improve data integrity and also simplifies reporting and analytics processes.

Embedded Collaboration

Embedded collaboration allows users to collaborate and communicate within the platform, enhancing teamwork and knowledge sharing. With embedded collaboration, teams can leave comments, annotations and suggestions on specific data sets or data assets. This feature streamlines communication and eliminates the need for external tools or email threads, making it easier for teams to work together effectively. With embedded collaboration, team members don’t have to constantly switch between data apps, which also saves time.

360° Data Profiles

Data catalogs that offer 360° data profiles allow users to access comprehensive information about a data set in a single view. The data profiles allow users to see who owns data, where it came from and other insights without having to search and spend time finding the information they need to know. This saves time on manual analysis and helps make data discovery more efficient.

Persona-Based Access Control

Persona-based access control features allow organizations to implement a granular level of control over who can access and view different types of data within the catalog. With persona-based access control, administrators can assign specific roles and permissions to different users based on their job functions and responsibilities. This ensures that only authorized individuals can access sensitive or confidential data, enhancing data security and compliance measures.

Programmatic Lineage Ingestion

Programmatic lineage ingestion enables organizations to automatically capture data lineage information from a variety of sources, such as data tools and platforms. This not only saves time and effort in manual lineage tracking but also ensures the accuracy and completeness of the data lineage. As mentioned, having a granular view of your data lineage is important for modern data governance, and programmatic lineage ingestion helps you get even more detail.

Data Profiling and Quality Assessment

Data profiling and quality assessment features in a data catalog are essential for ensuring that your organization's data is accurate and reliable. Data profiling and quality assessment can also help identify data privacy and security risks to help you adhere to compliance regulations. If these processes can be automated, you can also save your team time and tedious work.

SQL-Free Data Querying

SQL-free data querying should be one of the advanced search features your data catalog includes in 2024. Rather than making complex SQL queries to discover data, users should be able to search from an intuitive and user-friendly interface. This way, team members can make data-driven decisions regardless of their level of technical expertise.

Data Privacy

Data privacy has always been a concern, but it’s especially important with regulations like the GDPR and CCPA in place. Your catalog should provide features to protect your sensitive data and safeguard this information through encryption, access control and other security measures. Data privacy measures will help you adhere to compliance regulations and avoid losing customer trust.

Automated Lineage Generation

One of the most time-consuming and error-prone aspects of managing data is keeping track of data lineage. Data catalog software can automate this process by automatically generating lineage information. With automated lineage generation, you can quickly and accurately trace data from its source to its final destination, saving you time and mitigating the human-error factor.

Customizable Intelligent Automation

Automating some of your workflows and processes with your data catalog is helpful, but your modern catalog should also offer intelligent automation options. In other words, your team should be able to access customizable intelligent automation that not only allows users to tailor automation rules but also get smart suggestions on how processes can be improved. Automating tasks and leveraging AI to improve processes will lead to better data-driven insights and better business outcomes.

Dynamic Business Glossary

A dynamic business glossary allows organizations to define and manage business terms and their relationships within the catalog. This feature enables users to understand and interpret the meaning of data assets and how they relate to each other in a business context. A business glossary helps ensure users have a consistent understanding of data across the organization, along with its proper usage. A dynamic glossary should also allow users to see changes and activity logs, so users can view how definitions have changed over time.

Data Lifecycle Management

Finally, your data catalog should include data lifecycle management features. These allow organizations to keep track of data at each stage of its lifecycle, from creation to archival or deletion. With this feature, you can ensure data accuracy, improve compliance with data regulations and prevent data redundancy.


Data catalogs are central repositories for your data that make search and discovery easier, but that should be the bare minimum for your data catalog in 2024. Modern catalogs should offer you the features that a data-driven organization needs to truly leverage data and maximize its potential within your organization. If your data catalog isn’t performing up to current expectations, it may be time to consider a new solution.

Try Secoda for Free

Secoda is a data management platform that offers all of these features and more. It's the only all-in-one data search, catalog, lineage, monitoring, and governance platform to simplify your stack. Learn more about our platform today, along with its array of robust features. Schedule your demo to see how it works.

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