The IT term “big data” is currently getting close to the same hot-button treatment that cloud computing did five years ago, and for good reason.
The continued increasing amount of business data-created both by humans and by machines-is having major effects on IT systems, which are struggling to store, tier and make easily accessible all that information.
But it’s not just about high volumes of data. It’s also about the increasing number of data types that are coming into systems, which need to be handled differently from simple email, data logs and credit card records. It’s also about the speed at which all this data is moving from endpoints into storage.
Along these lines, IT researcher Gartner came out June 27 with a report that claims many IT decision makers are attempting to manage big-data problems by focusing exclusively on the high volumes of information-to the exclusion of the other facets of information management, which could lead to difficulties later.
“Today’s information management disciplines and technologies are simply not up to the task of handling all these dynamics,” said Gartner Research Vice President Mark Beyer. “Information managers must fundamentally rethink their approach to data by planning for all the dimensions of information management.
“The business’ demand for access to the vast resources of big data gives information managers an opportunity to alter the way the enterprise uses information. IT leaders must educate their business counterparts on the challenges while ensuring some degree of control and coordination so that the big-data opportunity doesn’t become big-data chaos, which may raise compliance risks, increase costs and create yet more silos,” he said.
Storage Not Handled Well Now Could Cause Big Problems Later
Gartner analysts warn that too narrow a focus will force massive reinvestment in two to three years to address the other dimensions of big data, Beyer said.
Worldwide information volume is growing at a minimum rate of 59 percent annually, Gartner said, and while volume is a significant challenge in managing big data, business and IT leaders must focus on information volume, variety and velocity.
Gartner defines those three “V’s” as follows:
Volume: The increase in data volumes within enterprise systems is caused by transaction volumes and other traditional data types, as well as by new types of data. Too much volume is a storage issue, but too much data is also a massive analysis issue.
Variety: IT leaders have always had an issue translating large volumes of transactional information into decisions-now there are more types of information to analyze-mainly coming from social media and mobile (context-aware). Variety includes tabular data (databases), hierarchical data, documents, email, metering data, video, still images, audio, stock-ticker data, financial transactions and more.
Velocity: This involves streams of data, structured record creation, and availability for access and delivery. Velocity means both how fast data is being produced and how fast the data must be processed to meet demand.
While big data is a significant issue, Gartner said the more important one is making sense of big data and finding patterns in it that help organizations make better business decisions.
“The ability to manage extreme data will be a core competency of enterprises that are increasingly using new forms of information-such as text, social and context-to look for patterns that support business decisions in what we call pattern-based strategy,” said Gartner Vice President and Distinguished Analyst Yvonne Genovese.
“Pattern-based strategy utilizes all the dimensions in its pattern-seeking process. It then provides the basis of the modeling for new business solutions, which allows the business to adapt. The seek-model-and-adapt cycle can then be completed in various mediums, such as social computing analysis or context-aware computing engines.”
More analysis is available in the Gartner Special Report “Pattern-Based Strategy: Getting Value from Big Data.”
Gartner is staging a webinar July 13 on the report. In it, Genovese will discuss the importance of applying a pattern-based strategy approach to seek, model and adapt to patterns contained in big data. The free webinar will be held July 13 at 9 a.m. EDT and noon EDT.
Go here to register for the webinar.