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Deriving Value from Big Data
Diverse data sets add to complexity but present new insights.
Posted Mar 20, 2013
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DALLAS—With customers, patients, and citizens now having more ways to interact with and influence the organizations they come into contact with every day, the role of businesses is becoming more complex.

Companies are tapping into social data and using it to leverage transactional sales data around purchases, as well as deliver marketing messages that could impact future buying habits, according to Rita Sallam, a research director for business intelligence at Gartner.

At present, 70 percent of organizations run analytical reports and dashboards on top of structured data sets. However, "we're seeing an increasing percentage of companies trying to do cause and effect type analysis," Sallam said during a presentation Tuesday at the Gartner BI summit.

Reliance solely on traditional data warehouse structures is shifting as advanced analytics emerge to measure unconventional data sources such as video, social media, text, speech, and networks. New sources of data are requiring salespeople to ask questions like, "Who is the key influencer?" Marketing will ask, "What ad should I present and when?" Customer or client services managers will ask, "What are my top ten product defects?" that affect customers, she explained.

One of the key elements in an enterprise's content analytics strategy is identifying new staff roles, responsibilities, processes, and skills to support analysis of emerging data sets. However, it's important to sustain past models, and "develop a plan to evolve current data management architectures, technologies, and processes to support new data volume, variety, and velocity requirements," Sallam said.


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