An IT focus solely on big data volumes misses the increasing opportunities from innovation and data strategies, according to a new report from Gartner.
Gartner pegs worldwide information volume growing at a minimum rate of 59% per year, according to its new report, “Pattern-Based Strategy: Getting Value from Big Data.” That amount of data has led many information managers to put inordinate importance on the amount of data, at the risk of hampering information architecture, creating more silos and compliance risks, and having big data strategies that might require massive reinvestment within two-to-three years, Gartner states.
Report authors Yvonne Genovese and Mark Beyer recommend three main topics for a successful big data initiative: volume, to find how data can be dealt with as storage or analysis issues; variety, for translating and discerning data sources; and velocity, to acknowledge the speed of incoming data and the speed needed to process demand.
Genovese, a distinguished analyst and VP at Gartner, says a measured approach to the actual data demands for business—rather than just the size of data sets—is central to harnessing ROI from big data, both at the enterprise and SMB-levels. This pattern-seeking process is meant for modeling for new solutions in mediums such as social computing analysis or context-aware computing engines, Genovese says.
She says big and unstructured data streams, particularly from social media and mobile devices, present opportunities similar to those from cost reduction and technological availability changes that occurred with ERP innovation.
“This is kind of the first time in industry history we’re seeing this, where the interest in business and the technologies are maturing at the same time in big data,” Genovese says.
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