Despite an abundance of data, enterprises often struggle to find quality data at the right time to empower them with actionable and accurate business insights. The impact of poor data quality on business performance is evident from Experian’s recent global survey where 95% of respondents indicated that poor data quality undermines business performance. A recent Gartner survey pegs the average annual cost of poor data quality at $12.8 million. Clearly, data quality directly impacts a range of business outcomes.
Ensuring data quality needs intervention at multiple levels. The five key steps organizations should take to protect good data and remediate poor quality data include:
Detect and log data quality issues
Enable data quality issue resolution and ownership
Fix the data and the root cause
Establish a data quality program
Define data quality outcomes and KPIs