It’s nothing less than ironic that at a time when virtually every initiative in the enterprise intersects with data, business leaders, including CIOs, seem to be somewhat blasé and poorly informed about how to arrive at quality data.
A new report from IT data intelligence firm Blazent and 451 Research, The State of Enterprise Data Quality 2016, reveals that only 40 percent of 200 IT decision-makers and influencers surveyed indicated they are confident about their organization’s data quality management (DQM) practices or the overall quality of data residing within their company.
This isn’t exactly reassuring and it doesn’t bode well for organizations. In fact, only 50 percent of the respondents believe the DQM practices their organization have in place—and the quality of the data they use—are much above a “slightly better than satisfactory” level or contributing to useful results.
All of this is unfolding amid a backdrop of rapidly swelling data volumes. Not surprisingly, 95 percent of the respondents expect the number of data sources and the volumes of data in their organization to increase in the coming year. Almost 70 percent believe data volumes will grow by up to 70 percent, while nearly 30 percent of respondents anticipate data volumes to surge by anywhere from 75 percent to nearly 300 percent.
At the center of the problem is a lack of strategic direction. According to the authors: “Organizations employ multiple means to manage data quality. Some of those means are surprisingly rudimentary and manual in nature.” Case in point: 44.5 percent of survey respondents admitted they find data errors from reports and then take corrective action to achieve DQM while 37.5 percent use a manual data cleansing process.
Incredibly, 8.5 percent of respondents avoided DQM completely, favoring a “hope for the best” approach.
Clearly, this isn’t the route to digital transformation or the path to positioning a company on the leading edge of innovation. In order to navigate today’s data environment effectively, organizations—and CIOs—must alter their mindset. Moreover, they shouldn’t depend solely on data scientists and data analysts to make sense of everything.
The report suggests that organizations expand rules and policies for MDM and all means of data capture; make those responsible for generating and capturing data responsible for data quality; introduce more transparent data environments; increase awareness about what “data quality” means; and deploy appropriate data cleansing and integration tools to close the loop.