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  • Intelligent machines part 2: Big data, machine learning and its challenges

    In the 1990s, average computers ran on megabytes of RAM and processing power under 100MHz, with hundreds of gigabytes of global Internet traffic being generated each day. Nowadays, RAM is in gigabytes and processing power is in the thousands of MHz, with hundreds of terabytes of Internet traffic per second.

    Written by Rebecca Merrett18 June 15 13:22
  • IBM commits to Apache Spark compute engine

    Calling Apache Spark "the most important new open source project in a decade that is being defined by data," IBM today announced that it will embed the compute engine into its analytics and commerce platforms and offer Spark as a service on IBM Bluemix.

    Written by Thor Olavsrud16 June 15 00:26
  • A quick rundown of how deep neural nets work

    Deep learning has proven to be a powerful method for going about artificial intelligence over the last few years, which has led to a growing interest in it across industries. So how does it generally work?

    Written by Rebecca Merrett12 June 15 15:16
  • Cascading big data framework gets Apache Tez support

    After about a year-and-a-half of development, big data application platform specialist Concurrent today released a new version of the open source Cascading big data application framework.

    Written by Thor Olavsrud10 June 15 23:54
Tutorials about big data
  • comScore CTO shares big data lessons

    comScore is no stranger to big data. The digital analytics company was founded in 1999 with the goal of providing intelligence to companies about what's happening online.

    Written by Thor Olavsrud30 June 15 00:28
  • 8 ways to make the most out of your customer data

    Everyone talks about the importance of big data. But many organizations, although they collect and store customer data, do not put that data to good use -- or they don't know how to.

    Written by Jennifer Lonoff Schiff16 June 15 04:20
  • Big Data ROI Will Take Time, Clear Goals and Talent

    The big data market is expected, by one estimate, to grow more than 30 percent annually until the end of the decade. But more than half of big data projects fail--and even those that do succeed can fall apart if the findings aren't applied to operational efficiencies. Ron Bodkin, CEO of Think Big Analytics, offers advice to help you prevent your business from becoming just another statistic.

    Written by Brian Eastwood22 July 13 14:45
  • 6 Big Data Analytics Use Cases for Healthcare IT

    Making use of the petabytes of patient data that healthcare organizations possess requires extracting it from legacy systems, normalizing it and then building applications that can make sense of it. That's a tall order, but the facilities that pull it off can learn a lot.

    Written by Brian Eastwood23 April 13 13:20
  • Big Data, Cheap Storage Bring In-Memory Analytics Into Spotlight

    In-memory analytics, like virtualization and the cloud, is an old idea that's been given new life. In this case, the combination of big data, inexpensive commodity storage and parallel processing make it possible to analyze terabytes of data without slowing systems to a crawl.

    Written by Allen Bernard06 Dec. 12 14:05
Features about big data
  • How to collect and analyze data from 100,000 weather stations

    If you want to understand what it takes to collect, track and analyze reams of data, just check the weather. There are constant fluctuations, scores of data points and intense interest from all over the planet. Analyze the data correctly and someone in the state of Washington knows whether or not to wear a raincoat. Do it poorly and there might be a massive traffic pileup from people driving too fast on slick roads.

    Written by John Brandon16 June 15 23:14
  • Big data companies argue their case at Demo Traction

    The recent Demo Traction event showcased a host of young companies that are gaining market momentum.  Each gave their pitch and then answered to a panel of judges.  If it is important for you to stay on the up and up with emerging technologies, this is must watch stuff.

    Written by John Dix08 May 15 06:10
  • How financial service firms use big data to meet business goals

    Most financial service firms, which includes banking and insurance companies, are engaged in a big data project to increase the pace of innovation and uncover game-changing business outcomes. The pressing challenge now is how to drive more continuous value and unearth opportunities more rapidly.

    Written by By Vince Dell'Anno and Brian McCarthy, Accenture Analytics26 March 15 02:19
  • Why businesses should focus on wide data, not Big Data

    In these heady days of Big Data, a lot of organisations treat data collection like a Pokémon game: Gotta catch it all. But Dane Atkinson, CEO of cross-platform marketing analytics specialist, SumAll, says most organizations need to think wide, not big, when it comes to data.

    Written by Thor Olavsrud14 March 15 02:23

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