Business Technology

Data Catalogs: A Vital Asset In Modern Data Management

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You can spend more time looking for data than you do analyzing it. In order to transform your business data into a competitive advantage, all your users need to be able to quickly find, understand, and utilize that data. If decision-makers across departments can’t find the data they need or can’t understand it, then they can’t leverage it to optimize business operations and improve key growth strategies. Businesses that establish a data catalog can easily discover, curate, categorize, and share data assets, data sets, and analytical models to uncover new opportunities. Data catalogs are becoming a core component of modern data management, allowing all business users to easily find and access data to accelerate time to insights.

What Is a Data Catalog?

A data catalog is a library where all your business data is neatly organized, indexed and kept ready for use. It organizes the technical details around data assets, or metadata, into defined, meaningful, and searchable business assets to enable consistent data understanding among all business users and data consumers.

What Does a Data Catalog do?

What data catalogs do is part of what a data catalog is – by organizing data from multiple sources into a searchable, centralized library, data catalog tools enable anyone looking for answers to their questions to locate, understand and utilize data more quickly and efficiently. But how do data catalogs do this?

Dataset Searching

Data catalogs offer robust search capabilities that include search by facets, keywords and/or filters, object name, and business term, making locating the right data faster and easier. Many data catalogs automatically rank search results by relevance and viewing frequency, so the best data is readily available.

Dataset Evaluation

The ability to preview a dataset, see all associated metadata, the user who certified the data, and descriptions as well as view data quality information simplifies the process of choosing the right dataset for an analysis.

Data Access & Protection

The data access functions ensure that users can access data compliantly and securely according to their needs. They include protection for security, privacy, and compliance sensitive data, so although everyone can access the same data catalog, only the users with the right permission will be able to access certain data sets.


A data catalog integrated with a business intelligence solution significantly improves the speed and quality of data analysis. It also provides a catalog of datasets and visualization features. With the right tool, advanced data operations would be also available.

Unified Management

Data catalogs eliminate silos for good. By providing a centralized location for your entire business data collection, data catalogs enable a self-service user experience and remove the burden on IT and data specialists to grant access to everyone that needs data and when they need it.

Why Your Business Needs a Data Catalog

According to research from IBM, business leaders spend 70% of their time finding data, and only 30% utilizing it. What good is your data if it’s not used to its fullest potential? Data is a valuable asset only if business users can transform it into meaningful and useful insights to drive their decision-making, derive value and gain a competitive advantage.

A data catalog makes data more accessible throughout your entire organization. Instead of your team having to rely on ITs and data analysts, they can use the catalog’s tools and find what they need in a matter of a couple of minutes. That saves time for everyone in the company, speeds up the decision-making process, and increases productivity and efficiency overall.

Data catalogs foster a data-driven culture. When everyone has access to data, then everyone across departments and responsibility levels becomes more confident and starts speaking the same language. Collaboration becomes easier and transparent. The goal of a data-driven culture is to bring transparency to the entire organization and provide easily consumable insights. It puts data at the center of all decisions, so you don’t rely on gut feelings, but instead on facts. That way, errors are shaved to a minimum and success is almost always guaranteed.

For example, if your business is in the retail industry and combines in-store shopper data, purchase history, and cell phone data, you can use that data to create and launch a geo-targeted ad campaign to potential customers at the point of purchase. Data catalog tools can help your team derive these insights, which can drive and support the ad campaign decisions. At the end, the data catalog enables a more effective ad campaign that retrieves a higher ROI.

Of course, collecting and storing data doesn’t come without any concerns and responsibilities about consumers’ privacy. Regulations about consumers’ data privacy are driving what data companies can collect and how they can store and exchange it. Data catalog tools help organizations stay in compliance with such regulations including GDPR, HIPAA, CCPA, and more.

Data Catalogs: Build or Buy?

It is absolutely possible to build your own data catalog. The question is whether it is worth the investment of time, money and effort, or whether it is better to invest in an already established data catalog tool. Here are the pros and cons of building vs buying a data catalog tool:

  • Building your own data catalog requires a dedicated team of data engineers – you’ll need a minimum of 5 engineers assigned to the project permanently, and even more during the building and implementation stages.
  • Building your own data catalog takes time – for big organizations with enough resources, the process of building their own data catalog could take around 3-4 weeks. However, some report that it has taken them multiple attempts and a couple of years until they finally managed to successfully set up the data catalog.
  • Data catalog standards change quickly; you need a maintenance and support team to keep your data catalog up-to-date – and that is on top of the initial project. You should either hire people to work on that only or add extra responsibilities to your existing team (and we guess they do have more important tasks to focus on).
  • To build your own data catalog, you need machine learning expertise to be able to capture technical, operational, business, and social metadata – data intelligence is crucial for the development of data catalogs and innovations like machine learning are at the core of it. Machine learning data catalogs (MLDC) provide the best possible way for managing, monitoring, and improving the use of business data assets and enable real-time data discovery, automated cataloging, crawling of metadata, and classification of PII data.
  • Building your own data catalog requires UX/UI resources – the goal of building a data catalog is that all of your users can easily find and access data. That means that the data catalog should be designed in a way that all users, regardless of role and expertise, can have a seamless experience working with it. To guarantee that, you’ll need a UX/UI expert working alongside the data engineers’ team.
  • Building your own data catalog is an expensive project – it may cost you less to build your own data catalog but in the long term there are many extra costs associated with this investment. You’ll likely pay 2x to 3x more to maintain your own tool than buying a data catalog with continuous updates and support costs built in.

Contrary, opting to buy an existing data catalog tool is the faster and more agile option. You can start leveraging it right away without worrying about hiring new people, burdening your data team or any maintenance and support. It makes sense to invest in a data catalog solution and let your engineers spend their valuable time working on software that improves your own product/service.

How to Find the Right Data Catalog Tool

The best data catalog is one that simplifies your data management process and helps your organization become more data-driven. Different data catalog solutions are suited for different use cases, so it’s important that you narrow your search to the ones that will best fit your requirements. Some handle data in data lakes and are more suitable for data science, while others are more business-oriented and therefore what you’re probably looking for.

But there’s more to choosing the right data catalog, of course. A data catalog is only as useful as its ability to search and filter data. If it is integrated into a data analytics solution such as Slingshot, it allows users to get the most out of their data and make smarter business decisions while simultaneously offering an extensive catalog of data sources & sets, visualizations and dashboards. It aggregates chat, and goal-based strategy benchmarking, data analytics, project and content management – all in one, a versatile and intuitive app.

A data catalog tool needs to have robust data search and discovery features so that all users can derive valuable insights from the data they work with. It should be able to leverage ML/AI to improve data literacy, accelerate time to accurate insights, and augment data preparation. It needs to be able to utilize pre-built connectors to a wide variety of sources, including an open connector SDK to connect to any other source, and incorporate collaboration. Make sure to also look for metadata curation, and what the vendor’s governance, compliance, deployment, and integration options are.


A data catalog should be the foundation of your data strategy. If you truly want to take control of your data and build one single source of trusted data that is easy to find, download, use and share, then a data catalog is the right tool. Gaining a unified view of all your data across your organization allows you to easily find the right data you need, and spend less time searching for it and more time analyzing it.

About the author


Dean Guida

Dean Guida founded Infragistics in 1989. Over the past 30+ years, Dean has grown the company to become a world leader in providing user interface development tools and multi-platform enterprise software products and services. He spearheads the Infragistics Innovation Lab and the Slingshot digital workplace platform.