Big Data Analytics Resources
Big Data Go-To Resources
- Inside IT: Big Data Podcast
- Intel IT: Advanced Analytics
- Intel® Cloud Builders Guide to Apache Hadoop*
Big Data for Business Intelligence
IT is challenged with deriving real meaning from data that could provide great business opportunity. Intel IT discuss developing the necessary skills & finding the right platform to deal with Big Data.Listen about big data business intelligence >
Intel IT has embraced a 5/6/10 model for prioritizing and assessing projects for maximum business value. This model deploys small 5 person BI teams for 6 months with the goal of delivering up to $10M of value.Download the advanced analytics roadmap >
Intel® Cloud Builders Guide to Apache Hadoop*
This reference architecture is for building cloud infrastructure, including both enterprise IT and cloud service providers or cloud hosting providers.Learn about cloud design and deployment >
Big Data Analytics Solutions
Big Data Vendor Spotlight: IBM
Bruce D. Weed talks about the key components of the IBM* big data platform—including the Intel® Xeon® processor E5 family. You’ll see how the company is using these solutions to help its customers build a smarter planet.Discover how IBM can help you build a smarter organization >
Big Data Vendor Spotlight: HP
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.Learn how HP can help you get return on your big data investment >
Big Data Vendor Spotlight: Oracle
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. See how Oracle’s technologies help you acquire, organize, analyze your data.Understand Oracle’s end-to-end approach to big data analytics >
Big Data Customer Examples
Genomic Sequencing Data
The University of North Carolina at Chapel Hill is using big data to find better treatments for patients through genomic sequencing technologies
Oct 2, 2014
University of North Carolina at Chapel Hill (UNC) analyzed big data from thousands of individual genomes to improve patient care and support research.Baca Selengkapnya >
Pecan Street uses data-driven analytics to empower consumers
Oct 2, 2014
Pecan Street uses data-intensive analytics to empower consumer energy management, collecting data using a device-to-cloud architecture.Baca Selengkapnya >
Chip Chats: Big DataListen to More Chip Chats >
- Database Appliance
- Big Data Analytics
- Database Performance
- Big Data in the Real World
- De-mystifying Big Data
- In Memory Big Data
Oracle Exadata Database Machine
Allyson chats with Tim Shetler, VP of Exadata Product Management from Oracle, about the Oracle Exadata Database Machine and its use in mission critical computing.
Oracle Exalytics In-Memory Machine
Marie-Anne Neimat, VP of Development for Embedded Databases, discusses the Oracle Exalytics real-time analytics product embedded into the hardware appliance and appropriate applications for deployment.
Database Performance on Intel® Xeon® Processor-based Platforms
Steve Shaw, Database Technology Manager at Intel, chats about database performance testing and engineering an Intel® Xeon® processor based system as a whole for optimal performance and scalability.
Real-world Uses for Big Data
Pauline Nist, GM of mission critical computing, talks about big data appliances, the Oracle Exalytics product for in-memory database, and real-world uses for analytics and mission-critical computing.
De-Mystification of Big Data
Mitch Shults, a mission-critical strategist, discusses the difference in structured databases vs. unstructured, delivering performance while managing latency, federated clouds, and in-memory databases.
In-Memory Database Processing with SAP HANA
Jeff Word, a VP at SAP, stops by to talk about SAP HANA, the first enterprise-scale completely native in-memory database. Keeping the database in RAM means that business data (point of sale, as well as Web 2.0) can be processed in parallel at real-time speeds
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