has greatly helped us to identify and address our data quality issues. Their team has become an extension of the AmeriGas team and that has helped us to move in the direction of continuous data monitoring, remediation of issues, and automation through machine-learning.”
US Companies lose over $3T in revenue and direct expenses annually as a result of poor or erroneous data.
25% of senior managers report spending up to a quarter of their day searching for data.
85% of senior managers believe their existing systems do not produce trustworthy data.
Receive our Data Quality Checklist which provides the 10 most common data quality problems.
The checklist includes questions to help you understand the specific data needs and challenges of your business.
Due to the complexity of data and its numerous sources, actual timeline for full implementation of our DQE will vary.