Big Data Requires Businesses to Embrace Innovation, Change: GartnerBy Nathan Eddy | Print
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Enterprises should start small with pilots that allow full transparency on the data, the analytics and the resulting insight.
Big data's ability to analyze unstructured data in large volumes and from disparate sources leads to innovative opportunities, but to get maximum value from the information, chief intelligence officers (CIOs) must realize that innovation needs to go well beyond the technology used to manage big data, according to a report from IT research firm Gartner.
The research indicated enterprises will need to seek and embrace innovation in the way business problems are analyzed with big data—generally referred to as a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.
"Big data requires an enterprise to embrace innovation on two levels," Hung LeHong, research vice president at Gartner, said in a statement. "First, the technology itself is innovative. Second, enterprises must be willing to innovate in the way they perform decision support and analytics. This second reason is not a technology challenge, but rather a process and change management challenge. Big data technologies bring innovative ways of analyzing existing business problems and opportunities. New data sources and new analytics can improve the enterprise in ways that have never been used before."
The report noted that in most cases, there has been very little precedence for the ways big data can add value to an enterprise and it was never possible to run these kinds of analyses or access these new types of data. Therefore, any business will need time to trust new data sources and new analytics and enterprises should start small with pilots that allow full transparency on the data, the analytics and the resulting insight.
"Perhaps CIOs feel more comfortable starting with internal data sources, because the thinking is that much of it is already being managed by IT," LeHong said. "However, in many cases, these internal data sources are not controlled by IT at all. For example, call center recordings, security camera footage and operational data from manufacturing equipment all represent potential internal sources of data to investigate, but they are usually not under the control of IT."
Enterprises that use big data technologies can afford to keep the full, raw data, building up rich sources of data that can provide new insight, the report said. However, CIOs will need to ensure that there is always a clear business purpose and outcome for storing this new data. Although technology may enable faster speed, getting business value from that speed often requires process changes, and Gartner research indicated that early adopter enterprises that implemented faster analytical capabilities changed their processes to get the maximum benefit from the speed.
"CIOs must ensure that big data projects that improve analytical speed always include a process redesign effort that aims at getting maximum benefit from that speed," LeHong concluded. "Before pursuing big data investments, ensure that the evaluating team has a clear understanding of how faster analytics will lead to an improved business outcome—and build this into the business case."