How to Choose the Best Enterprise Data Catalog: Key Criteria Uncovered

It's analyst report season! In the next few months, analyst firms will provide guidance on how to approach the data catalog market and key criteria for choosing a data catalog. These reports can be helpful starting points. But they should be just that: a starting point. With over 12 years of experience and a customer base of nearly 600 enterprises, including 40 of the Fortune 100, we've developed a comprehensive understanding of what truly matters in a data catalog solution to deliver business success. Here are our key criteria uncovered:

Real-world Validation: Outcomes

When evaluating an "enterprise" data catalog, the number of successful enterprise deployments should be a crucial consideration. When evaluating vendors, leaders should ask: How many organizations have implemented the data catalog across their entire data infrastructure? What are the statistics on deployment sizes—mean, median, max, and min? How many people within that enterprise use it each day?

These metrics reveal the catalog's scalability and ability to handle extensive data, analytics, and AI environments, as well as, ultimately, the scale of the impact being driven. 

Another critical factor is the breadth of the deployment and the catalog's ability to support the data query needs of different enterprise personas, Can your chosen data catalog support the needs of business users, data analysts, data stewards, data scientists, and data engineers? As Geraldine Wong, CDO, said, “In an ideal data culture, everyone—from the board to the CEO, from finance to HR—would instinctively turn to data for insights.”

Enterprise Readiness

Security: Protecting Your Data

It’s important for leaders to understand: Is the data catalog in compliance with the latest, most stringent security standards? 

For enterprises serious about security, partner with a catalog vendor that has compliance certifications, including SOC 2, ISO 27001, and FedRAMP.

AI Functionality: Reality vs Rhetoric

While AI capabilities are highly valued, it's essential that the catalog you choose offers AI features that ensure trust and understanding. Ask: Does the AI generate useful and accurate content, or does it flood the system with low-quality data? Whenever generative AI capabilities are integrated within a platform, it’s important to realize the significance of the training and the quality of the AI functionalities. To gain the most productivity from AI, it needs to be methodologically implemented within a platform to provide value.

At Alation, everything we introduce is “machine-suggested” and “human-verified” to ensure that the data experts still create the biggest impact in curating data asset types. Humans must be in the loop to account for hallucinations or supplement contextual knowledge. Our generative AI models utilize Amazon Bedrock to power AI, ensuring secure and efficient interactions with the service while keeping customer metadata safe. Customer content is not used to train models nor shared with third-party model providers while staying encrypted in transit and at rest. 

Quality and Integration: Beyond Data Quantity

Today, it's not just about having more data; it's about the quality and integration of that data. For this reason, leaders should ask: Are data quality tools seamlessly integrated with the catalog? Will we be forced to use a data quality tool as part of a vendor’s suite, or will we have the choice to use the preferred data quality tool that best fits our needs? Can we leverage multiple approaches, and gain a comprehensive view of data quality across the enterprise? 

An open and extensible integration framework ensures that data remains accurate and reliable across the organization. Customers should have the freedom to choose the best data quality tools that seamlessly integrate with the catalog platform. 

By leveraging custom data quality tools, organizations can ensure high-quality data for better analysis, compliance, and data management. Partnering with a catalog vendor with an open API framework facilitates integration, allowing users to access crucial data quality information, such as rules, metrics, and alerts, streamlining the data quality and governance processes.

GPI review of Alation from a data leader in retail, praising the UI and data quality integrations

Head of Data Engineering in the Retail Industry gives Alation Data Intelligence Platform 5/5 Rating in Gartner Peer Insights™ Data and Analytics Governance Platforms Market. To read the full review here, click the image.

Choose a Business Success Partner, Not a Technology Vendor

Purpose-Driven Cataloging

What is the purpose of your future data catalog? Today, organizations face a wide range of use cases, from data governance and AI to self-service analytics and data modernization. For this reason, leaders should ensure that in addition to looking at features, they are also answering the following questions: What will we try to do with our data catalog? What is the outcome we seek? How will we deliver on it?

The catalog's value should be measured by its ability to support specific use cases. Whether those use cases are AI model implementations, cloud data migration, or scaling data governance, the use case you choose should be well supported (with customer validation) by the data catalog you ultimately select. 

A Gartner review of Alation from a D&A director in consumer goods praising the rollout and implementation

Director of Data and Analytics in the Consumer Goods Industry gives Alation Data Intelligence Platform 5/5 Rating in Gartner Peer Insights™ Active Metadata Management Market. To read the full review here, click the image.

Measuring Success

Leaders should ask catalog vendors: How do you roll out the catalog? How do you define and measure its success? What are the best practices for ongoing adoption?

Alation’s approach to implementation is structured, collaborative, and iterative to ensure successful adoption and integration within an organization. 

Program support and user engagement are critical factors. Look for a partner that enables customers to measure data culture growth and success through an assessment. These assessments help organizations evaluate their data culture maturity. The Alation data culture maturity model is a great tool to measure success. 

A user community within your organization is extremely important to ensure ongoing adoption. The Alation Community enhances an end user’s ability to leverage the platform effectively and fosters a collaborative environment for knowledge sharing and innovation across the organization.

Gartner review from a taxonomist in healthcare praising the product's community and training support

Taxonomist in the Healthcare and Biotech Industry gives Alation Data Intelligence Platform 5/5 Rating in Gartner Peer Insights™ Data and Analytics Governance Platforms Market. To read the full review here, click the image.

Data Governance

Leaders should ask questions about the catalog vendor’s approach to data governance. Is data governance viewed as a means to block people from data and restrict access? Or is it a way to enable people to use data more efficiently and intelligently, with the appropriate guardrails to ensure compliance?

As regulations grow in complexity, organizations need a way to integrate data governance into the workflows of every person who needs data to do their job. Data bottlenecks are a real risk. Legacy approaches to data governance risk creating a high wall around valued data, dividing people into two groups, the data “haves” and “have nots.” By selecting a data catalog that eases data democratization, leaders can ensure data governance does not restrict access but instead streamlines appropriate usage. 

Gartner review from enterprise architect praising Alation's data governance capabilities

Enterprise Architect in the Miscellaneous Industry gives Alation Data Intelligence Platform 5/5 Rating in Gartner Peer Insights™ Data and Analytics Governance Platforms Market. To read the full review here, click the image.

Conclusion

When considering an enterprise data catalog, there is much more to driving success and ROI than specific features and functions. You should consult the analyst research available on the market, but it’s also important to think about your requirements and what vendors offer, including products, services, and repeatable success methodologies, to decide what is most important. Your business's unique needs and how you define data-driven success should influence the catalog partner you ultimately choose.

Alation is a proven leader with a broad, experienced point of view, having consistently delivered value to nearly 600 customers in this market for the past 12 years. We have learned that the best catalog isn't one that tries to be all things to all people but rather one that aligns with clear goals and provides a solid foundation for data-driven success.

Are you curious to learn how Alation can help you deliver a data culture? Book a meeting with us or read this report to learn more.

    Contents
  • Real-world Validation : Outcomes
  • Enterprise Readiness
  • Choose a Business Success Partner, Not a Technology Vendor
  • Conclusion
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