Data governance, data integrity, and data quality are all widely used terms, but what do they actually mean and how are they connected? The purpose of this article is to provide a structured model for ...

As there are many misconceptions associated with realizing data quality, here are three important data quality myths and their corresponding realities.

Allowing quality data in can lead to a better understanding of an organization. Read more to improve your data quality for unstructured data.

The goal of data governance is to ensure your organization’s data is business-ready: high-quality, accessible, secure, and ...

Poor data quality can damage your reputation and hamper your business. Here are strategies to help you detect, correct and prevent bad data.

The marketing world is driven by data, but its quality is of major importance. Avoid bad data practices and learn the advantages of high-quality data.

Key findings show organizations averaging just 42/100 on data trust maturity, with the lowest scores in areas such as remediation workflows, policy enforcement, and reference/master data quality.