Bruce D. Weed, program director of Worldwide IBM Big Data Business Development, talks about the key components of the IBM big data platform*—featuring the Intel® Xeon® processor E5 family. Learn about the four main components of IBM big data: IBM InfoSphere BigInsights*, InfoSphere Streams*, InfoSphere Information Server*, and data warehouse appliances. Find out about the top use-case scenarios for the solution, including a close look at how one of IBM’s customers reduced modeling time from weeks to hours.
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Irshad Raihan explains how HP solutions for big data, built on the Intel® Xeon® processor family, deliver value quickly and cost-effectively to companies analyzing both structured and unstructured data. Take a closer look at the HP solutions that are helping them overcome those challenges. You’ll also learn more about the two recent acquisitions that allowed HP to deliver powerful analytics software. And you’ll see how all these technologies work together to give you proven return on your investment through insights we derived from structured data, additional insights provided through unstructured data, and the initiatives that your organization is able to put into action thanks to those insights.
Learn how HP can help you get return on your big data investment >
Kimberly Billings and Manan Goel from Oracle explain how Oracle big data solutions deliver a uniquely integrated, end-to-end approach to big data acquisition and analysis. Get an overview of the company’s big data technologies, including Oracle Big Data Appliance*, Oracle Big Data Connectors*, and the Oracle R Enterprise* component. Learn more about the Oracle Exalytics In-Memory Machine*—the industry's first in-memory analytics appliance. Find out how Oracle’s engineered systems, Exadata*, Oracle Exalogic Elastic Cloud*, and Exalytics* are specifically designed to take advantage of Intel® x86 architecture.
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Omer Trajman, vice president of Technology Solutions at Cloudera, talks about how his organization is making major contributions to Apache* open-source projects, Cloudera’s own Hadoop* distribution, and how these efforts are helping organizations profit from all their data. Learn how and why they continue to develop the open-source, big data technology that’s proven and widely in use. Take a closer look at these technologies, including Cloudera’s distribution including Apache Hadoop (CDH), Cloudera* Enterprise, Flume, Hive*, Pig Latin, Oozie, ZooKeeper*, Hue, and Mahout*. Then you’ll learn how these solutions work together to help you analyze your big data in real time. From there you’ll get an idea of the training, customization, and support you need to take full advantage of big data.
Learn about how Cloudera is contributing to open-source big data solutions >
Paul Kent, vice president of Big Data at SAS, explains that combining their industry-leading analytics software with high-performance computing technologies produces fast and precise answers to previously unsolvable problems—and enables customers to gain greater competitive advantage. SAS high performance analytics include SAS Grid Computing*, SAS In-Database*, and SAS In-Memory Analytics*, all of which are optimized for Intel® Xeon® processors.
Learn how SAS high-performance analytics solutions address big data challenges >