Kuala Lumpur (22 September 2014) — Investment in big data technologies continues to expand, according to a recent survey by Gartner, Inc., which found that 73 percent of respondents have invested or plan to invest in big data in the next 24 months, up from 64 percent in 2013. The survey also indicates organizations are starting to get off the fence about their big data investment — the number of organizations stating they had no plans for big data investment fell from 31 percent in 2013 to 24 percent in 2014.
The Gartner survey of 302 Gartner Research Circle members worldwide, which was conducted in June 2014, was designed to explore organizations’ technology investment plans relating to big data, stages of big data adoption, business problems solved, data, technology and challenges and compare the results with those from previous years.
“Big data investment continues to be led by North America, with 47 percent of organizations reporting investment, up from 37.8 percent in 2013. On the other hand, Asia Pacific reported an increased investment in big data of about 35 percent indicating that organizations are evolving in terms of their understanding and willingness to explore big data opportunities,” said Nick Heudecker, research director at Gartner. “All other regions experienced increases in investment over the last year.”
However, this increased investment has not led to an associated increase in organizations reporting deployed big data projects. Like 2013, much of the work today revolves around strategy development and the creation of pilots and experimental projects.
“Last year, we said 2013 was big data’s year of experimentation and early deployment,” said Mr. Heudecker. “So is 2014. In 2013, only eight percent of organizations reported having big data projects deployed to production. This has increased to 13 percent in 2014, and while still relatively small, represents a sizeable increase. However, the six percent drop in organizations still gathering knowledge about big data and the seven percent increase in pilots and experiments indicate that organizations are exploring big data opportunities.”
“Big data can help address a wide range of business problems across many industries and for the third year in our study, both enhancing the customer experience and improving process efficiency are the top areas to address,” said Lisa Kart, research director at Gartner. “The most dramatic changes are in enhancing customer experience, especially in transportation, healthcare, insurance, media and communications, retail, and banking. Another area where we see an increase is using big data to develop information products, where organizations are looking to monetize their data. This is especially true among IT vendors, government and manufacturing.”
Gartner continues to see strong investments and planned investments across all vertical industries with communications and media continuing to lead the pack with 53 percent of organizations surveyed having already invested and a further 33 percent planning investments in big data technology.
The other year-to-year changes in the survey findings are a function of the adoption stage. As organizations move beyond knowledge gathering and developing a strategy to making investments, piloting and deploying, the challenges they face become more practical. Those with no big data plans feel the big hurdles are determining how to get value from big data, defining a strategy, leadership or organizational issues, and even still trying to understand what big data is. In the planning stages, beyond determining value, the top challenges are obtaining skills and capabilities needed, defining strategy, obtaining funding, and beginning to think about infrastructure issues. Companies that are further along with investments must begin to address risk and governance issues, data integration and infrastructure.
When it comes to the volume, variety and velocity aspects of big data, volume received most of the focus. Increasing data volume is easily understandable: you’re getting the same data you had before, but at massive scale. Volume is also the easiest to deal with by increasing storage and compute capacity. On the other hand, data variety is far more challenging. Getting value from a variety of data sources, such as social media feeds, machine and sensor data, as well as free-form text, requires not only increased storage capacity, but also different tools and the skills to use them.
The challenges introduced by analyzing a variety of data sources may explain why most organizations are studying traditional data sources for their big data projects. Those organizations analyzing transactions increased from 70 percent in 2013 to 79 percent in 2014, while those analyzing log data fell slightly by two percent. Interestingly, both types of social media data sources — profiles and interactions — fell over the last year, which may be caused by the difficulty in integrating social media data sources with other types of data, such as transactions.
“We got a surprising result when we asked respondents which data sources they planned on adding in the future,” said Mr. Heudecker. “Every data source received roughly 30 percent to 40 percent of responses, including extremely challenging data sources like audio and video. This overly optimistic and apparently random nature of future data sources for analysis indicates two things. First, organizations don’t have a plan for what they’re going to do next. Picking everything isn’t a strategy. It indicates a fear of missing out on an opportunity yet to be defined. Also, there may be a certain amount of hubris at work. If organizations can ‘do big data’ on transactions and log data, they may assume they can also leverage more challenging data sources as easily.”