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  • Accelerate Apache Spark to boost big data platforms

    Big data platforms like Apache Spark process massive volumes of data faster than other options. As data volumes grow, enterprises seek ways to speed up Spark. Continue Reading

  • Big data users share their trying but winning analytics war stories

    The challenges encountered in deriving business benefits from big data are huge, but so are the rewards. Hadoop and related technologies are easing those challenges to the point where companies are willing to graduate from experimental to full-blown big data analytics deployments. Still, the march toward that goal can be long and arduous, and not just from a technological and architectural standpoint. Before taking the plunge, big data users, including data scientists, managers and evangelists, are faced with the sometimes monumental task of justifying big data's return on investment to business executives focused on competition, profit margins and allocation of funds. "For a lot of organizations like ours, big data has not yet become a core foundation of running the business," said Beata Puncevic, director of analytics, data engineering and data management at Blue Cross Blue Shield of Michigan. Yet, actionable insights gained from big data analytics can be indispensable in driving revenue, reducing costs and developing new products.

    This handbook on big data analytics examines the trials and tribulations of big data users who are on the front lines, devising and implementing partial and full-blown applications. In the first feature, editor Craig Stedman interviews battle-tested IT and analytics warriors from Blue Cross, Macy's and Progressive Insurance who reveal the business challenges in justifying the worthiness of big data applications. In the second feature, Stedman explains how real-time big data analytics is helping companies like Comcast and eBay to move quickly on massive amounts of incoming information. And in the third feature, reporter Ed Burns spotlights the decisions at Neilsen and Nasdaq to run or not to run big data systems in the cloud.

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  • Tomorrow's not yet today for IoT data analytics

    The outlook for the internet of things is about as huge as the amount of data it's being asked to gather and analyze. By 2020, Gartner says we can expect to see 13.5 billion IoT-connected devices and IDC estimates the amount of information produced by IoT technologies will account for 10% of the total data generated from embedded systems. Even today, IoT data analytics offers a potential treasure trove of information that companies can use to formulate marketing campaigns, reduce operating costs, streamline manufacturing processes and influence product development. Yet organizations are approaching the IoT with a good bit of caution, hoping to avoid being overwhelmed by the massive amounts of incoming data. Adding to their cautious approach are a lack of industry standards, concerns about protecting customer information and confusion over what kinds of data are valuable to collect.

    In the cover story of June's Business Information, editor Lauren Horwitz writes that IoT's promise and present-day reality are out of alignment and cites two companies using IoT data analytics with an eye toward managing the resultant explosion of information. "If we started big, it would take us forever to deploy and we'd get more data than we'd know what to do with," says Hexagon Manufacturing Intelligence's business development manager for user experience and innovation.

    In another feature, editor Craig Stedman details how Highmark Health uses predictive maintenance software to keep its printing and mailing process running 24/7 without interruption. "We really can't afford to be down at all," says the output services director of HM Health Solutions, a subsidiary of Highmark Health. Stedman then examines ThyssenKrupp Elevator, which is in the early stages of launching predictive maintenance applications to avoid unplanned service outages on its elevators.

    Also featured in this issue is an HR manager who automated her company's ancient employee performance review process with the help of talent management software and the comic strip Dilbert.

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