Understanding Poetry at the HPE Big Data Conference

HPE’s Big Data Conference was given the tag line #SeizeTheData which immediately made me think of the wonderful film “Dead Poets Society.” One of my favorite scenes is when the students learn how to measure and analyze poetry. You can refresh your memory of the dialogue by watching this clip  or reading here. Of course, the whole point is that using analytics doesn’t work in poetry appreciation. Which I thought made #SeizeTheData rather ironic as a hashtag. Yet as the event rolled on, HPE themselves declared that “drawing a line through a cloud of dots” isn’t the point of big data; rather it should augment human intelligence. I noticed that analytics could in fact be applied with human passion and human wisdom almost anywhere for human good. Uber detailed how they are bringing rides to underserved communities, and reducing traffic and pollution in cities, all driven by analytics. Similarly positive work is being done with big data applications in healthcare, communications, and many other industries. To read the complete article, CLICK...

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IBM BigInsights: Refining Open Source Big Data…

I’ve written pretty regularly about IBM’s history of promoting open source technologies. Those efforts began with the company’s support of Linux in the 1990s, resulting in IBM supporting Linux distributions across its entire portfolio of systems and other solutions. Over the years, the company also contributed and invested extensively in a wide range of existing and emerging open source projects. Plus, it open sourced some of its own home grown technologies, including the Eclipse development platform and the Power microprocessor architecture. But it’s also worth considering the tactical purpose behind those efforts, and the resulting benefits that have accrued to IBM and its customers and partners. That’s especially true considering the company’s recently announced IBM BigInsights 4.2 platform and the related IBM Big Replicate solutions. To read the complete article, CLICK HERE NOTE: This column was originally published in the Pund-IT...

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“Big data, huh, what is it good for?…

The mood of this week’s Hadoop Summit has felt wonderfully diverse. There is a cognitive disconnect between the incremental progress of dot release feature sets and the revolutionary new business and societal applications of the technology. In the same keynote session the topics can swerve from optimizing cluster utilization to optimizing marketing yields to finding a cure for cancer. The technical lectures were packed, while the expo floor was focused. A loud rock and roll string trio in (unnecessarily short) black dresses exits the stage to be replaced by serious talk of open-source projects and community. One day a presenter will explain how clever they are to be able to apply pervasive surveillance of drivers for more profits, the next day a keynote is focused on rallying the audience to develop their ethics and fight the forces of ignorance. Is the Hadoop Summit about vendor announcements or business outcomes? Is it about infrastructure or applications? Is it “sex sells” or cubical contributions? Is it profit or politics? Ultimately, it seems the big data industry is struggling to define who will benefit and how from our new technologies. If I had to pick some winners and losers, here would be my list. To read the complete article, CLICK...

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EMC, Dell, Pivotal, Microsoft, and … Ford?

Last week was interesting. I spent most of it in Las Vegas at EMC World, which was as much about Dell as it was about EMC itself. There was a ceremonial handoff from Joe Tucci to Michael Dell to lead the new combined entity, but Jeremy Burton was perhaps even more in the spotlight as he outlined the vision. Much of this vision was about the balance between traditional data center environments and something he called “cloud-native” applications. Substituting “next-gen” for “cloud-native” might be more accurate, as this category included everything from PaaS to big data to containers to hybrid clouds. Hadoop, Cassandra, and MongoDB were cited as examples as cloud-native, which felt odd. Certainly they are cloud-friendly, but they’re by no means exclusively cloud-centric. See my last post on cloud big data for more thoughts on this topic. To read the complete article, CLICK ON AUTHOR’S...

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Data is Getting Boring Again

For the last five years, the term “big data” has evoked heady dreams of transforming business as we know it. The use cases were as broad and brash as as the imaginations of senior executives. Data scientists became rockstars and could name their own salaries. New approaches to storage and analytics, including distributed workloads on commodity hardware with open-source software, meant the performance and economics of extracting insights from data was radically shifted. The future’s so bright, we’ve got to wear shades. To read the complete article, CLICK...

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