New technologies, such as Hadoop, use a map/reduce paradigm that enables parallel processing of massive volumes of differently structured data that is spread across potentially hundreds and thousands of nodes. This breaks down the analysis of seemingly unmanageable data volumes into small discrete analytics jobs, and then the reduced result sets are combined to provide the complete answer. This IBM® Redbooks® Solution Guide is intended to help organizations understand how IBM InfoSphere® BigInsights™ for Linux on System z® and other related technologies can help deliver improved business outcomes as part of a big data strategy.
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Information is power if you know how to extract value and insights out of it. The more that is known about a particular issue, situation, product, organization, or individual, the greater the likelihood of a better decision and business outcome. Data is like oil because it can be refined and used in many different ways, increasing its market value. Unlike oil, however, it is a renewable resource.
This material has not been submitted to any formal IBM test and is published AS IS. It has not been the subject of rigorous review. IBM assumes no responsibility for its accuracy or completeness. The use of this information or the implementation of any of these techniques is a client responsibility and depends upon the client's ability to evaluate and integrate them into the client's operational environment.