IT Brief NZ - Gartner: Enterprise spends big money on Big Data...

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Gartner: Enterprise spends big money on Big Data...

Investment in big data technologies continues to expand, with 73 percent of decision-makers either investing or planning to invest in big data in the next 24 months, up from 64 percent in 2013.

According to Gartner findings, organisations are starting to get off the fence about their big data investment — the number of organisations stating they had no plans for big data investment fell from 31 percent in 2013 to 24 percent in 2014.

"Big data investment continues to be led by North America, with 47 percent of organisations reporting investment, up from 37.8 percent in 2013," says Nick Heudecker, research director, Gartner.

"All other regions experienced increases in investment over the last year."

However, this increased investment has not led to an associated increase in organisations 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," Heudecker adds.

"So is 2014. In 2013, only eight percent of organisations 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 organisations still gathering knowledge about big data and the seven percent increase in pilots and experiments indicate that organisations are evolving in their understanding and willingness to explore big data opportunities."

Big Data... Big Money

Lisa Kart, research director, Gartner adds that big data can help address a wide range of business problems across many industries and for the third year in the study, both enhancing the customer experience and improving process efficiency are the top areas to address.

"The most dramatic changes are in enhancing customer experience, especially in transportation, healthcare, insurance, media and communications, retail, and banking," Kart adds.

"Another area where we see an increase is using big data to develop information products, where organisations 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 organisations 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 organisations 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 organisational 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 analysing a variety of data sources may explain why most organisations are studying traditional data sources for their big data projects.

Those organizations analysing transactions increased from 70 percent in 2013 to 79 percent in 2014, while those analysing 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," Heudecker adds.

"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, organisations 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 organisations can 'do big data' on transactions and log data, they may assume they can also leverage more challenging data sources as easily."

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