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Advanced analytics tools extract business value from big data
Sponsored by IBM
This chapter is included in the Big data initiatives get huge boost from new technologies E-Book.
Big data environments based on technologies such as Hadoop and Spark are being deployed more widely -- and the same goes for advanced analytics tools that can help organizations make effective use of the data flooding into those systems. In fact, predictive analytics software was the top choice for planned business intelligence and analytics investments by respondents to a TechTarget survey.
And in many cases, deployments of advanced analytics software to support big data applications aren't a one-and-done thing. Macy's uses more than a half-dozen tools to meet different application needs as part of the retailer's big data analytics program. The technology roster includes statistical analysis, predictive modeling and machine learning tools that Macy's couldn't do without. "Because of the volume of data, there's just no humanly possible way to analyze it [manually]," said Seetha Chakrapany, the company's director of marketing analytics and customer relationship management systems.
Macy's is just one of six organizations featured in this e-book chapter by Executive Editor Craig Stedman. Progressive Casualty Insurance Co. is another. The insurer's data and analytics business leader, Pawan Divakarla, said the capabilities provided by advanced analytics tools are "huge" in enabling Progressive to manage a program for awarding discounts on auto insurance policies to safe drivers based on analysis of operational data collected from their vehicles.
But there are issues to contend with along the way, from the complexity of developing predictive models and machine learning algorithms to the challenge of sharing analytics results with business executives. Find out how Macy's, Progressive and others have overcome the hurdles and made advanced analytics against pools of big data work successfully.
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