Big data software could be a key growth area for resellers, with Ovum predicting the market will grow nearly six-fold by 2019.
The technology research and advisory firm says while big data software is just a small part of the overall market for information management in 2015, it is set to increase at a compound annual growth rate of 50% through to 2019, and play an increasingly important role that will position big data analytics as a core capability for many enterprises by 2019.
Tom Pringle, Ovum practice leader and co-author of the Ovum Software Market Forecasts: Information Management 2015 report, says the experimental era of big data is coming to an end, with organisations formalising their use of big data technology to realise the business value they expect to find.
“Big data, as an open source technology, has been accessible without creating huge financial impact on the market,” Pringle says.
“Ovum believes that situation is changing, with commercial Hadoop distributions and a fast-growing ecosystem of enabling and extending technologies pointing toward a bright future for big data.”
The overall market for information management software is also growing at a significant CAGR of 11%, the report says, with business intelligence and analytics also contributing to the strong growth and close to doubling in 2019, from a market size of US$15.8 billion in 2015.
Pringle says self-service business intelligence, which enables a whole new universe of users, is driving the expansion of the market.
“With easier to use self-serve tools becoming mainstream, and moves to the cloud and mobile providing accessibility, barriers to growth in this market are being eroded,” he says.
The report says day-to-day data management remains the largest part of the market, accounting for more than 40% of total spend at US$24.1 billion
“Even as the biggest dollar spend on information management, data management continues to grow strongly, with a CAGR through 2019 of 9%,” Pringle says.
“This expansion speaks not only to the growth in data volumes, but in particular the newer challenges of managing a much more heterogenous range of data types and the speed with which those data are generated.”