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The Big Data Challenge: Social Data Meets Corporate Data

With the rise of social media sites, companies are getting hit with a blizzard of unstructured data, and must now find cost-effective ways to integrate and analyze the collective pool of big data to generate granular business insights.

With the rise of social media sites such as Facebook and YouTube, companies are getting hit with a blizzard of unstructured data. This data onslaught comes on top of rapid growth in the amount of customer data housed in enterprise systems. Companies now must find cost-effective ways to integrate and analyze the collective pool of big data to generate granular business insights.

A recent Intel white paper may have said it best: "We are in the midst of a revolution in the way companies access, manage, and use data. Simply keeping up with the explosive growth in data volumes will be an ongoing challenge, yet the true winners will be those that master the flow of information and the use of analytics throughout their value chain." ¹

To stay on top of it all, many companies are deploying Hadoop, an open-source parallel processing framework, to process and analyze social media data on distributed server clusters. They then integrate Hadoop with systems housing other customer data to gain rich insights. To support these efforts, solution providers are building Hadoop interfaces into database products to help with the performance of big data delivery, management, and usage.

What we have here is the intersection of the traditional methods of delivering, managing, and viewing information and a new approach that allows data of all types and formats to be quickly sorted for transactional and operational opportunity. This new era of data exchange requires next-generation compute, storage, and I/O technologies-like those found in the Intel® Xeon® processor E5 family.

This next-generation processor family is a great platform for running analytics on big data in private cloud solutions and enterprise data centers, as well as in cloud deployments. The raw compute power of the processors enables efficient, intelligent, and secure archiving, analysis, discovery, retrieval, and processing of critical data. And along with fast processing, the Intel Xeon processor E5 family accelerates throughput with PCIe 3.0 technology and Intel® Integrated I/O, which is designed to dramatically reduce I/O latency and eliminate data bottlenecks across the data center infrastructure.

On the storage side, the Intel Xeon processor E5 family incorporates accelerated RAID and Intel' AES New Instructions (Intel® AES-NI) to speed data encryption. This latter technology is particularly important in private cloud environments, where pervasive encryption is used to protect data from hackers and other threats.

The new Intel architecture also incorporates innovative technologies designed to reduce power and cooling costs and enable dense configurations with thousands of processors. This is a perfect chip for blade environments.

If your organization is moving ahead to the new architecture from the Intel® Xeon® processor 5600 series, Intel has a good ROI story to tell, on top of the performance story. And if your organization uses systems based on earlier-generation processors, the new Intel architecture can deliver spectacular ROI while moving you further along in your journey to the cloud.

While it's a great chip for cloud environments, the Intel Xeon processor E5 family is also ideal for private clouds and enterprise data centers looking to accelerate the processing of large datasets while driving down the cost of computing. It's up to the challenges of big data.

Pauline Nist is a general manager in Intel's Datacenter and Connected Systems Group. You can reach her on Twitter @panist

Pauline is a 25+ year industry server veteran. Currently Pauline is General Manager for Enterprise Software Strategy at Intel. Previously Pauline was Sr. Vice President of Product Development and Product Management for Penguin Computing. Pauline has an MBA from Clark University, was part of Yale's Executive Management Program, and has a Bachelors of Science in Mathematics from University of Pittsburgh.

¹ Insight Everywhere: The Growing Importance of Big Data and Real-Time Analytics. Intel white paper. 2012.

The above insights were provided to InformationWeek by Intel Corporation as part of a sponsored content program. The information and opinions expressed in this content are those of Intel Corporation and its partners and not InformationWeek or its parent, UBM TechWeb.



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By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



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