12 Actions Data and Analytics Leaders Can Take to Improve Data Quality – A Gartner® Report

Data and analytics leaders are facing more pressures–and opportunities–than ever before and trusted, high-quality data is key to capitalizing on them. Yet, many data, analytics and AI initiatives fail because of poor data quality. 

Poor data quality costs organizations an average of $12.9 million every year¹ and this situation is likely to worsen as business operations and data ecosystems become increasingly complex. Organizations that don’t have impactful and supportive DQ programs in place will face a multitude of complications and lost opportunities.

Download the report to explore key findings like:

• Data quality (DQ) programs overemphasize solving technical data issues without a connection to organizational impact, thus failing to help key business stakeholders achieve their business outcomes.
• Organizations often take an imbalanced approach to DQ improvement, typically adopting a technology-first approach while investment in modernizing DQ practices lags behind.
• Many organizations do not have a decision rights model to support data and analytics (D&A) governance and are therefore unable to hold business areas accountable for the quality of their data.
• D&A leaders that fail to address key areas — such as information culture, enabling roles and business processes in DQ initiatives — are perceived by business areas as transactional service providers rather than critical business partners.

Access this complimentary Gartner report to assess your data quality maturity and gain 12 simple and pragmatic actions to build an effective data quality program that enables better business results.

1. Gartner: Survey of reference customers for the 2020 Magic Quadrant for Data Quality Solutions.