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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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  • Cloud streaming analytics prescribes big data remedies

    It seems like everything's in motion these days. Streaming data is no exception. With the avenues of information proliferating, it's critical that companies extract value from incoming data in real time, enabling them to devise successful business strategies and remain competitive. IDC reports that the amount of data created is growing at a burgeoning rate of 40% annually and will reach 44 trillion gigabytes by 2020. Needless to say, collecting, storing and analyzing this data can require a nonstop effort of herculean proportions. Cloud streaming analytics can help companies get a better grip on that relentless endeavor and mine true business value.

    In the first feature of this guide, News Writer Joel Shore reports how Time Warner Cable used real-time cloud streaming analytics as a service to gain better insight into its customer base and identify new marketing opportunities for its clients. The second feature by Shore raises the question of whether big data is too big for cloud-based analytics. While companies amass and store large amounts of data, the percentage of collected data that's actually accessed for analytics purposes is alarmingly microscopic. In the third feature, IT consultant Swathija Raman delineates five principles of mastering software analytics, logging and reporting in relation to the internet of things and how these principles apply equally to a multitude of business formats.

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  • Operational intelligence technologies are making real time a reality

    While many take the traditional route to business intelligence, forward-thinking companies are taking a more operational approach. By integrating BI and analytics, these companies are enabling improvements of business processes -- in real-time. Rather than looking backward, consultancy Ventana Research says these organizations are looking at the present in an effort to “detect and respond to events as they are happening.”

    In this three-part guide, SearchBusinessAnalytics explores operational intelligence initiatives at organizations and examines their impact on business processes in customer service, logistics, energy and manufacturing. First, TechTarget executive editor Craig Stedman details the recent stream processing deployment at RelayHealth, which runs claims processing applications for healthcare providers. The company recently turned to Apache Spark to provide more real-time analytics to clients. Next, consultant David Loshin looks at specific business processes that can benefit best from operational intelligence tools and techniques. Loshin also tackles some of the “challenges to making it all work.” And in an interview, Rick Sherman, founder of consultancy Athena IT Solutions, offers insight into the benefits and potential problems of operational intelligence efforts. Continue Reading

  • Streaming large video files in today's big data environments

    Solid-state drives are a good choice for streaming large video files. Other factors to consider include cost and how often video will be accessed. Continue Reading

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