Discover Insights on the State of Enterprise Data Quality

High-quality data is no longer a nice-to-have or a when-we-get-to-it—in 2024, it’s an imperative in the enterprise. The growth of privacy and compliance regulations, the business value of data democratization, and the rise of generative AI are all driving enterprises to seek better solutions for data quality.

At Anomalo, our aim is always to better understand our enterprise customers and their workflows and incorporate these insights into our product. We recently commissioned the independent firm Dimensional Research to capture the state of enterprise data quality through a quantitative survey. Download the executive brief.

Who was surveyed: 300+ people with responsibility for data quality at enterprise companies with at least $1B USD in revenue. Titles included data leaders, data scientists, data engineers, and data architects.
What was evaluated: The survey asked about the importance of data quality, the extent to which teams are investing, and the problems they’re seeing with existing tools.

Key survey highlights:

• 95% have had a data quality issue with a direct impact upon business outcomes — confirming that data quality is more than just a technical issue
• 95% agree that data observability alone is not enough to determine the root cause of data quality issues
• 87% say that traditional rules-based approaches to data quality don’t scale to meet today’s needs

Today’s teams are facing complex data architectures, an increase in data volumes, and a growing number of external data sources. It’s no surprise that 100% of the participants surveyed are combatting quality issues in their data warehouses and data lakes. What else we’re taking away: enterprises benefit from automated root cause detection that looks at data values—scaling beyond rules and observability. They’re seeking comprehensive data quality solutions that empower cross-functional teams to collaborate toward resolution.

Download the executive brief for additional insights on the state of enterprise data quality.