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Data gravity is becoming an ever-more-powerful force in data center environments. In this view, it makes more sense to analyze data where it has the greatest density – which is often in on-premises databases or data repositories. This “data gravity” perspective is all about a new option to aggregate data in a cloud provider’s infrastructure, allowing it to scale to the petabyte stage, and analyzing that large dataset using high-bandwidth, low-latency fabrics.   The term “data gravity” was coined by Dave McCrory two years ago, based on the physics of gravitation. McCrory, who had worked at VMware and Cloud Foundry, started...
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The world of analytics is expanding – and the complexity is expanding right along with it. Data is stored in distributed file systems, on clustered server nodes, and on scale-up systems. It may be structured, or unstructured, data. And, applications that access the data can be written to run on physical servers, virtual servers (VMs), or containers. The result is a rapidly growing, complex environment for customers. IBM’s approach to addressing these customer issues is to provide a new generation of advanced resource-management IBM Spectrum Computing software that supports software-defined infrastructure (SDI). The SDI functionality abstracts the control plane away from...
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Is Data Quality Relevant for Big Data?

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One of the biggest benefits from a big data analysis is the ability to find answers to new types of questions and then quickly take action to improve business results. For example, a retailer can leverage social media data to analyze customer reaction to a marketing campaign and make immediate changes rather than waiting several weeks to review results from traditional marketing data sources. Various big data sources such as Twitter feeds, audio files, or emails are analyzed and the resulting patterns that emerge can provide important business value for companies. Increasingly, leaders understand there is enormous value in integrating...
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  In researching our new book, Big Data for Dummies, it became clear that Big Data is not simply about a specific tool or technique for Big Data analytics.  You would never know this by examining the hype around this emerging market.  Yes, Hadoop is important but it not the entire big data ecosystem.  Big Data is not one tools or manipulating and analyzing huge volumes of data. And Big Data is not about calculating how many individuals on Twitter or Facebook mentioned a certain event.  It is easy to get caught up in the hype and focus on the tools...
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Looking for the Small in Big Data

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While the buzz in the big data market is around massive amounts of data and what you can do with that data, in truth companies are more interested in the small stuff. Let me explain. One of the greatest benefits of getting hold of lots of data is that a company can see patterns and anomalies that would have gone undetected with a smaller set of data. Companies are interested in big data not so much because of what that data represents in terms of volume, variety and velocity, but what the analysis of that data can do for the business....
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What is the big deal about big data?

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I have begun writing a weekly blog for Bloomberg BusinessWeek. I am pleased to be able to republish my discussions on my blog site. In this blog I discuss the value of big data and its implications for the business. Your comments on this blog are welcomed.   The ability to analyze mountains of data is important, but managers need to be wary of suppliers relabeling a traditional product as new technology    ...
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