According to the report, less than half (40 percent) of C-level executives and data scientists are very confident in their organization’s data quality, with the majority (94 percent) recognizing the impact poor data quality has on business outcomes.
Two key disadvantages are lost revenue (42 percent) and bad decision-making (39 percent).
“The lack of faith in data quality management was surprising, in spite of the clear need for it.
Business users do not have a clear sense of the breadth and depth of the data quality problem in spite of the fact that they are continuously exposed to the effect of bad data,” Gary Oliver, CEO of Blazent, told in an interview. “Also, I was somewhat surprised at the lack of alignment between line of business and IT groups, considering they’re two eggs in the same basket.”
Oliver said given the amount of data coming in from too many directions, and given that the existing tool sets and IT infrastructure mechanisms are clearly overwhelmed, the results are easy to understand, if a bit surprising.
“There needs to be a more systematic and proactive alignment between line of business and IT management in support of quality data–and therefore information–in order to make effective business decisions,” he said. “The challenge for data migration is that migrating anything to the cloud is a complex job that needs to be done while the business continues to run at increasingly faster speeds. Not unlike changing the tires on a moving car, except this car has billions of wheels and is moving so fast you can’t see it.”
When asked about root causes for poor data quality, nearly half (47 percent) cited data migration as a leading cause. Read More…