This solution brief summarizes the content of the technical white paper called, "Perform Predictive Analytics and Interactive Queries on Big Data".
Recent innovations in data warehousing and business analytics dramatically increase the capability and potential value of today’s massive, diverse, and often fast-moving data flows. Companies now perform interactive queries and predictive analytics using all available data, including operational data and the huge amounts of poly-structured data available from logs, social networks, sensors, and many other sources. In this white paper, we define a practical, cost-effective infrastructure for supporting data-driven decision-making on an enterprise scale.
The business potential of big data analysis is enormous across virtually every business sector. The Intel IT organization has implemented use cases delivering hundreds of millions of dollars in business value. This paper discusses a few of those use cases and the technologies and strategies that make them possible. It also defines the architecture we use for big data analysis and provides an in-depth look at one of the most important components—an Apache Hadoop* cluster for storing and managing large volumes of poly-structured data.
I attended the Cloud Expo in New York City at the Javits Center in June. The attendees were a mix of Web hosting companies, web developers, software developers, hardware developers, and operating system developers. The event sponsors included Intel®, IBM*, Citrix*, Rackspace*, Oracle*, Verizon Terremark*, Akamai*, and many more. Everyone came to learn, share, and we agreed that the development cycle was quicker than expected for new software and products using the.
This Configuration and Deployment Guide explores one of the leading Not Only Structured Query
Language (NoSQL) database, Cassandra, on Intel® Architecture. The configuration guidelines address
use cases with both Intel Xeon® processor- and Atom™ processor-based servers that take into account
differing business scenarios, performance requirements and Total Cost of Ownership (TCO) objectives.
Just a quick note to say that I arrived this morning in San Francisco to participate in IDF 2013! I find it all very exciting... I am speaking on the tomorrow afternoon on Intel Platform technologies and the cloud, going to use Meshcentral.com as an example of how anyone can leverage Intel technologies to make cloud services better. Information about my session:
The STREAM benchmark (http://www.cs.virginia.edu/stream/) a synthetic benchmark program, written in standard Fortran 77 (with a corresponding version in C). It measures the the performance of four long vector operations. These operations are:
name kernel bytes per iteration | FLOPS per iteration
COPY: a(i) = b(i) 16 0
This Configuration and Deployment Guide explores designing and building object storage environments based on OpenStack* Swift* in cloud environments, where responsiveness and enery costs are critical factors. High-performance, energy-efficient microservers, such as those based on the latest generation of Intel® Atom™ processors and Intel® Xeon® E3 processors, meet these requirements. The guide uses data from recent benchmarks conducted by Intel® Software and Services Group on Intel Atom processor and Intel Xeon E3 processor-based microservers.
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