Expectations for enterprise big data investments are set to grow this year, with the majority of companies forecasting increased focus and spending in this area in order to meet growing business demands.
This is according to a new study from TEKsystems, which revealed more than six out of ten IT leaders (61 per cent) predict an increase in spending in 2015, compared with just five per cent who plan to scale back investments.
Faith in companies' ability to meet big data demands is also high, with 59 per cent of respondents saying they are positive about their results, while only 14 per cent express a lack of confidence.
Despite this optimism, there remain some difficulties, and one of the biggest challenges faced by businesses this year will be addressing a shortage of skills in big data-related fields. This is leading to many organisations looking for external assistance when it comes to either training their existing employees in new technology, or hiring new experts.
The hardest role to fill was said to be big data architects, with almost two-thirds of IT executives (65 per cent) saying finding these professionals poses challenges. Also in the top three were data scientists (48 per cent) and data modelers (43 per cent).
TEKsystems noted: "The data analysis, data wrangling and algorithm expertise that big data architects and data scientists possess represent a very scarce skill set as compared to the more mainstream big data developers and administrators."
It added that given the challenges companies face when dealing with growing data volume, velocity and variety, it is unsurprising that strategic roles are in high demand, as they are crucial when it comes to identifying data with the highest business value.
David Spires, director in TEKsystems' applications division, commented: "There is certainly immense value in big data, but without great people and a focus on the workforce, the prospects that big data can deliver will unfortunately rarely be realised."
He added that too often, organisations do not evaluate what their workforce needs will be until it is too late, which leads to big data projects not providing their expected return on investment.