- 62% of data professionals reported that their average time to detection for data problems was five to eight hours.
- According to 47% of respondents, poor data quality had a negative impact on at least 25% of their business’s sales.
Previous industry surveys have indicated that most data professionals still have trouble with poor data quality despite the effort and money spent on improving it. A data dependability company, Monte Carlo, collaborated with Wakefield Research to poll over 300 data professionals to learn more about the condition of data quality in the more significant industry. The goal was to build on these findings and aid data leaders in understanding where and how to invest resources.
The study’s findings demonstrate that teams struggle with data quality and waste valuable time, money, and resources trying to resolve problems. In general, respondents said they spend 40% of their time assessing or verifying the quality of the data. Additionally, more than 50% of respondents said that spending the most time each day creating or fixing pipelines took a lot of time.
62% of data professionals reported that their average time to detection for data problems was five to eight hours. Resolving data incidents took nine hours on average.
Insights about data quality
Poor data quality was also demonstrated to impact revenue, according to 47% of respondents, who said it negatively impacted at least 25% of their business’s sales.
Here is what the report of the 300 data professionals noted:
- Finding a data quality incident takes 75% of people four hours or longer.
- Almost 50% of respondents claimed that once the problem has been located, it takes an average of nine hours to resolve.
- According to 58% of respondents, the overall number of incidents has increased slightly or significantly over the previous year. This is frequently due to more complicated pipelines, larger data teams, higher data quantities, and other causes.
- There is some good news, though. In the next six months, 90% of respondents said they would be investing in data quality solutions like data observability, either presently or in the future.
More than 300 data professionals were contacted through email between April 28 and May 11, 2022, to participate and complete this online survey.