Big Data. Big Decisions
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How Fusion-io Makes The World's Data Go Faster

Fusion-io exec describes how the company's hardware and software enable data center managers to build faster, more cost-effective storage arrays, in the latest episode of Valley View.

Gary Orenstein, Fusion-io's senior VP of product, says his company's purpose is to make the world's data go faster. Data is everywhere--the cloud, the Web--but it's on disk, which is too slow for many of today's demanding data needs. With Fusion-io's IoDrives and Ion Data Accelerator software, data center managers can build solid-state, flash-based storage arrays across physical and virtual servers more cost effectively. And it does so with a smaller footprint, which is crucial in today's data center.

Orenstein says Fusion-io is doing lots of work in organizations using Oracle, Microsoft, and MySQL databases, and is also starting to see some big data deployments using MongoDB.

Orenstein boiled all of this down into his 3-minute elevator pitch on Valley View recently and came out shining in front of our judges. You can watch it all in the video embedded below.

Make sure to tune into our October Valley View, on October 24 at 11 a.m. Pacific Time, where we'll have more startups--including Taptera (enterprise mobile applications), Alteryx (big data), and Hearsay Social (social enterprise). We'll also feature conversations with Cisco CEO John Chambers, and Oracle president Mark Hurd. You can also register for the October Valley View show and have a chance to win some excellent gear.

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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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