Blog - Data Quality

What did we learn from Esri UC 2025? A lot. From Utility Network readiness to system modernization and partner enablement, the conversations at our booth revealed how integration has become the foundation for everything. Dive into four major themes shaping the future of GIS — and how the Geonexus Integration Platform is helping organizations stay ahead.

There’s one thing that’s always shared between every member of a utility: the importance of data quality in their roles.

Data integration is vital to the success of organizations in asset-intensive industries like transportation, utilities, telecommunications, and more.

Learn why performing a robust data cleanup before integration is crucial. Plus, discover common data error patterns to look out for in the data clean up process.

According to Gartner, organizations found that poor data quality results in $15 million per year of losses. Don’t let bad data derail your organization. Discover how your organization can eliminate the hidden costs of bad data.

Don’t let the asset swap out process wreak havoc on your organization’s data quality and integrity between GIS and EAM systems. Learn how your organization can get ahead of this issue.

Data quality drives the reliability of data-driven decisions and is therefore paramount to any organization, particularly asset-intensive organizations. Read about three ways that enterprise system integration can help improve data quality.

What is Enterprise Data Integrity? The definition of enterprise data integrity is the consistency and accuracy of common data across multiple enterprise systems. The key questions being, do you trust your data of critical decision-making?