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Data Center Management | Intel® Datacenter Software

Intel® software for data center management enables new IT capability, storage, and optimization, with open source solutions for next-gen applications.

Amplify DB2* Performance with IBM and Intel® Innovations: Brief

Solution Brief: IBM DB2* 10.5 running on the Intel® Xeon® processor E5 family delivers high performance, flexibility, and cost savings.

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Intel Chip Chat: SAS Perspective on Big Data Analytics

SAS Vice President of Big Data Paul Kent discusses SAS’s approach and how the market will look in five years after integrating analytics.

Intel Chip Chat: SAS on Data Visualization

SAS’s Paul Bachteal discusses data visualization growth, delivering self-service data analytics without IT dependence for faster real-time insights.

Distributed Data Mining and Big Data: Intel Vision Paper

Intel’s perspective on distributed data mining with big data—or the analytics of big data generated by sensors and devices on the edge of networks.

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Computer on Wheels Project Connects Students with Technology

The Computer on Wheels project brings computer labs to students in Pakistan, connecting students with technology and making learning fun.

Infografica sulla sicurezza della mobilità aziendale: aiutare il reparto IT a scegliere i dispositivi

Infografica sulla sicurezza della mobilità aziendale: un'introduzione visuale per aiutare i responsabili IT a scegliere i dispositivi portatili ideali per incrementare la produttività della loro azienda.

Data Center Management | Intel® Datacenter Software

Intel® software for data center management enables new IT capability, storage, and optimization, with open source solutions for next-gen applications.

T-Systems Creates a Cloud-Based Big Data Solution

Case Study: T-Systems deploys an Intel® Xeon® processor-based big data cloud, enabling new data analysis services while optimizing energy efficiency.

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DuPont Eyes Hadoop* for Bioscience Data Growth

White Paper: DuPont demos Intel® Distribution for Apache Hadoop* proof of concept, shrinking bioscience data for linear scalability, reduced workload.

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