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Past industry surveys show that a lot of data professionals have a problem with poor data quality, regardless of the period of time and resources committed to fixing it. To expand on these insights and help data leaders understand where and how exactly to invest resources, data reliability company, Monte Carlo, partnered with Wakefield Research to survey a lot more than 300 data professionals to reveal hawaii of data quality in the broader market.
Results from the analysis show that teams remain struggling with the standard of data and wasting time, money and resources to repair conditions that arise. Respondents reported that normally, 40% of their own time is spent evaluating or checking data quality. Additionally, over fifty percent of respondents ranked building or fixing pipelines as taking probably the most level of their time during the day.
When data incidents occurred, nearly all data pros 62% said their time and energy to detection was five to eight hours. The common time for resolving data incidents was nine hours.
Data quality and underneath line
Poor data quality was also shown as affecting underneath line with 47% of respondents estimating that bad data affected 25% or even more of these company revenue.
Of the 300 data professionals surveyed:
- 75%take four or even more hours to detect a data quality incident.
- About 50 % said it requires typically nine hours to solve the problem once identified.
- 58% said the full total amount of incidents has increased somewhat or greatly in the last year, often due to more technical pipelines, bigger data teams, greater volumes of data, along with other factors.
However, there’s some positive news. Roughly 90% of respondents reported these were already investing or likely to spend money on data quality solutions, like data observability, within half a year.
The survey greater than 300 data professionals was conducted between April 28 and could 11, 2022, utilizing an email invitation and an paid survey.
Browse the full report from Monte Carlo.
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