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Organizations increasingly collect Web server logs, social media data, information from sensors and other forms of unstructured data -- and then looking to use them in combination with structured transactional data to improve business operations and gain a competitive edge over competitors. In this chapter of our e-book on managing and using pools of big data, readers will find in-depth advice on planning and implementing successful big data analytics projects that produce tangible business benefits. Access >>>
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Big data environments bring a mix of new technologies into organizations, including Hadoop, MapReduce, NoSQL databases and associated tools. And ...
In this chapter of our e-book on managing and using pools of big data, readers will benefit from expert tips on integrating data in Hadoop systems ...
Technological buzz, like that surrounding Hadoop, can easily blur the lines between software benefits and drawbacks. Hadoop clusters make it easier ...
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Predictive analytics capabilities allow for top-notch big data modeling
Building effective analytical models is a key facet of big data analytics applications -- though doing so is easier said than done.
This e-book ...
Market trends tell the future of predictive analytics deployments
Predictive analytics employs statistical or machine-learning models to discover patterns and relationships in data, thereby enabling the prediction ...
Machine data equals big value for analytics programs
Sensors capture large volumes of data about the operations of industrial equipment; similarly, log files gather huge amounts of information about ...