According to the 2019 Data Decisions Survey from analytics database provider Exasol, 57% of organisations have suffered because of slow or poor access to the right data, resulting in an inability to access real-time analytics and accurate business intelligence (BI).
Of more than 1,000 IT decision makers surveyed, 80% reported that data guides organisational decision making more than 50% of the time, yet significant performance, security and forecasting challenges impede the ability to improve data strategy.
The biggest data strategy barriers: security, costs and performance
The survey revealed that data security (39%), high costs (38%) and slow data performance (31%) were the biggest obstacles to data strategy. For respondents leveraging cloud data warehouse solutions, including Oracle and Amazon Redshift, slow data query performance (30%) and lack of support for hybrid deployments (23%) were the biggest issues faced when configuring their solution.
“Demand for data is exploding, and new technologies, such as cloud analytics, MPP or in-memory analytics make it feasible to realise a data-driven company,” said Mathias Golombek, CTO, Exasol. “However, organisational challenges, combined with a complex technology landscape and limited legacy systems, are holding organisations back from realising the full potential of their data. These findings demonstrate an industry ready for data-driven change, without access to the tools they need to achieve it.”
Avoid vendor lock-in for improved data analytics and performance
When asked what they would like to change about their organisations’ data strategy, respondents indicated improved ease-of-use when integrating data from various sources for better analytics performance (44%), more forward-looking analytic insights, such as recommendation, predictions, forecasts (43%) and for their organisations to make data ready for analysis at a faster rate (37%). In the meantime, more than 60% of respondents feel stifled by vendor lock-in, which may be holding them back from their data goals.
“Outdated legacy data warehouse solutions that fail to support hybrid and on-premise deployments, scale poorly and have slow data performance are not the answer to today’s exciting data opportunities,” said Golombek. “A powerful operational analytics layer on top of a well-designed and governed data lake will make organisations empowered to get more out of their data, let more people get access to insights, and apply more complex analytics on larger data sets.”
Additional survey findings include: