Bigeye Expands Data Quality with Advanced Enterprise-Ready Features

Custom dimensions, cross-database join rules, and column-level asset linking modernize enterprise data management without losing existing data quality value.

SAN FRANCISCO , CA, UNITED STATES, October 1, 2025 /EINPresswire.com/ -- Bigeye, the leading enterprise data observability platform, today announced a new set of advanced data quality features designed to help enterprises modernize their data management practices while continuing to leverage the rules and processes they already rely on.

These new enhancements include customizable data quality dimensions, join-based rules across databases, and column-level asset linking—enabling enterprises to embrace the benefits of data observability without losing the value of their existing body of data quality rules.

CUSTOMIZABLE DATA QUALITY DIMENSIONS
Bigeye now allows customers to tailor how data quality is defined and reported within their organizations. While the platform includes core dimensions such as pipeline health, completeness, uniqueness, validity, and distribution, enterprises can now configure which metrics and rules roll up into each category. This flexibility helps teams ensure that data quality reporting reflects their unique governance and compliance requirements.

JOINS AND JOIN RULES
With support for joins across multiple tables—even spanning different databases—Bigeye enables the creation of rules that capture data quality issues that only emerge in relationships between datasets. Enterprises can now enforce integrity checks across systems, ensuring that joined data remains accurate and trustworthy throughout the data lifecycle.

ASSET LINKING FOR PRECISION REPORTING
Bigeye’s new asset linking capability makes it possible to associate specific metrics and rules with individual columns. For example, a rule involving multiple tables can be reported only against a critical data element (CDE) that resides in one of the tables, ensuring that data quality results for that CDE align with existing reporting structures.

MEETING ENTERPRISE NEEDS TODAY AND TOMORROW
These innovations are helping large enterprise organizations migrate from legacy data quality platforms onto Bigeye for data observability. By delivering compatibility with existing rules while introducing more advanced data observability capabilities, Bigeye helps enterprises not only preserve the value of their current investments but also accelerate their transition to a more automated and scalable future.

“Enterprises don’t want to throw away years of investment in legacy data quality practices just to modernize,” said Kyle Kirwan, Chief Product Officer at Bigeye. “With these new capabilities, Bigeye makes it possible to carry forward existing rules and processes while also unlocking the benefits of advanced data observability.”

Enterprises can now gain the best of both worlds - preserving institutional knowledge in data quality while positioning their data quality strategy for the future by leveraging a scalable data observability platform.

Discover how Bigeye can help you migrate from legacy data quality solutions to a modern data observability platform. Explore our case studies to see how we’ve helped other enterprises, or get a personalized demo and learn how we can support your data management needs.

About Bigeye
Bigeye is the data observability platform for large enterprises. Bigeye helps data teams in some of the world’s largest companies detect, prioritize, and resolve data incidents before they impact the business. Only Bigeye has data observability that is powered by comprehensive data lineage and AI-driven resolution and prevention to improve data reliability across modern, legacy and hybrid data stacks. Bigeye is trusted by top enterprise organizations such as USAA, Zoom, Hertz, Cisco and Freedom Mortgage to ensure the data powering their business stays reliable by default. To learn more about Bigeye, visit www.bigeye.com.

Jesse McCabe
Bigeye
+1 303-868-0081
email us here

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