Businesses’ quest to adopt a data-driven culture is being hampered by a failure to extract the data insights decision makers need to turn their dreams into reality and, more worryingly, senior management’s misunderstanding of data strategy.
According to new research commissioned by analytics database company Exasol, over two-thirds (68%) of data teams are unable to extract the right data with 80% of data decision makers blaming their current IT infrastructure, which, they claim, makes it hard to democratise data, further limiting their ability to extract value from insights.
The Data Strategy and Culture: Paving the Way to the Cloud report, reveals nearly all (96%) of respondents believe a cloud model can make it easier to democratise data in their organisation.
Meanwhile, nearly three-quarters (73%) state that migrating some or all data workloads to the cloud had a positive impact on what they can do with their data. Of these respondents, half (51%) report that the cloud has improved ease of access and shareability of data, and 46% cite faster query response times.
Exasol chief technology officer Mathias Golombek said that many businesses are only scratching the surface of what is possible with their data. Any organisation with an infrastructure that slows down data access for its teams has a fundamental problem, he explained.
Golombek added: “Four out of five decision makers in our study have reported performance issues. This is unacceptable. 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 survey further revealed that decision makers perceive a lack of data strategy understanding at the senior management level (40%) and widespread (52%) resistance to the adoption of data-driven methods. The study also found additional disjointed approaches to data strategy, culture, IT infrastructure and cloud migration as potential causes of this problem.
Golombek continued: "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.
“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."