Study Finds Most Data Teams Can’t Always Extract the Insights Needed for Better Decision Making
New survey results also reveal enterprise concerns over their data strategy, culture, IT infrastructure, and cloud migration.
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New research commissioned by the analytics database company Exasol reveals that 68 percent of data teams are unable to always extract the data insights needed by their organizations’ decision makers. The inability to access insights is hindering business’ ability to become truly data-driven, something they must achieve if they are to stay ahead of the competition. The report, “Data Strategy and Culture: Paving the Way to the Cloud,” also found that 80 percent of data decision makers say their current IT infrastructure makes it hard to democratize data, further limiting their ability to extract value from insights.
According to the research, almost all (96 percent) respondents believe a cloud model can make it easier to democratize data in an organization. Almost three-quarters (73 percent) say that migrating some or all data workloads to the cloud had a positive impact on what they can do with their data, including improved ease of access and shareability of data (51 percent) and faster query response times (46 percent).
"Many businesses are only scratching the surface of what’s possible with their data. Any organization with an infrastructure that slows down data access for its teams has a fundamental problem. Four out of five decision makers in our study have reported performance issues. This is unacceptable,” says Mathias Golombek, Exasol’s CTO. “You can’t be a data-driven business if your teams can’t work with the data or if it takes them too long to find what they need.”
The report revealed that decision makers perceive a lack of data strategy understanding at the senior management level (40 percent) and resistance to the adoption of data-driven methods (52 percent). The study also found additional disjointed approaches to data strategy, culture, IT infrastructure, and cloud migration as potential causes of this problem.
“Putting data strategy first is essential to making sure that businesses can move at a speed they want to, rather than a speed they are forced to by an infrastructure decision. That’s why the choice of deployment model must come after establishing a clear data strategy and an effective data culture,” said Golombek. “How your people feel about working with data is a big part of the equation. Limitations can cause frustration and prevent your teams from becoming truly data-driven.”
The survey of over 2,000 data strategy decision makers in the U.K., Germany, the U.S., and China was conducted by Sapio Research. Respondents work in a broad range of business roles, from C-level to marketing and operations, and are all responsible for gathering or applying insights from data.