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How to manage video surveillance retention – the biggest Big Data

This BURA Sunday, we welcome guest blogger Jay Jason Bartlett, VP WW Sales and Marketing, SoleraTec, now a member of the HP Data Agile Partner Program.


Camera.jpgFrom the Boston Marathon bombings to daily law enforcement video security in the U.S., our society has become conditioned to video surveillance, almost to the point of expecting video to be available. Whether it is traffic cameras, shopping mall cameras, warehouse cameras, or now the very popular police body-worn cameras, video surveillance – and the storage of all that video – is seeing significant double-digit growth.


But what is the best way to reliably and cost efficiently retain these ever-growing amounts of video surveillance feeds? A new multi-tiered storage solution from HP and SoleraTec enables a complete scalable video surveillance infrastructure capable of providing years of video surveillance storage at costs no longer out of reach. Let’s take a closer look.

The Game Show Network Games and Big Data

Nth Symposium was a few weeks ago and one of the keynotes was delivered by Portman Wills.  Portman is the Chief Data Scientist at the Game Show Networks Games.  Portman discussed how they log every action taken by gamers and with HP Vertica, they use that information to improve their users' experience and drive higher revenue. 


For me, the keynote did a great job of making big data real and specifically how HP Vertica is used to get the insights that Portman discussed.  So Portman graciously said yes to my request to talk to him (he had a flight shortly after his keynote ended) and I think you'll find this as interesting as I did. 

Labels: Big Data| Nth2014

Which 5 IT areas look to prosper in 2013?

By Andre Carpenter, senior solutions architect


Here’s to 2013! It’s a very exciting time to be in IT—and especially in the storage, cloud and virtualisation space. Last year saw a massive shift in the IT landscape as CIOs really started to show interest in this thing we call cloud computing. More focus on how things can be done better and more cost effectively was one of the prominent drivers behind this surge in interest.


Crystal Ball.jpgLooking into the crystal ball…

I’ve never deemed myself to be a fortune teller of any kind, but I guess in some wacky kind of way it is part of my role: possessing a grasp of what’s happening now and an ability to translate this and interpret the market to foretell what might be happening 6 months, 12 months, 18 months down the track. This is always a beneficial skill for any IT professional to have. This time of year, we see a number of predictions on market trends that appear to be obvious for 2013. Then there are some that may come as a surprise. So let’s take a look at some of the areas that I think will prosper.

HP ProLiant SL4500 for Big Data

SL4500.pngPrior to HP Discover, my server brethren announced the HP ProLiant SL4500 - a new server based product that was positioned for "big data".  I was working to get a podcast with a couple of guys on the team when we realized that we'd all be at HP Discover together so I offered to do a video with them in their booth.  That turned out to be a great choice because seeing is believing - or I should say is understanding. 


I also have a ChalkTalk giving a high-level architectural overview of HP StoreAll that should help you understand the data services it offers and how it's different from the SL4500. 


The best big data presentation I've ever seen

Noumenal_BigData.pngI saw the best presentation I've ever seen on big data at the Nth Generation Symposium last week.  The session was delivered by Marc Demarest, Founder & Principal of Noumenal, Inc.  Marc didn't talk about big data from a vendor perspective but from a customer perspective.  After Marc's session, I grabbed him before he could get out off the stage and asked to do a podcast with him, which he graciously did.  This is a fantastic overview of his session.  This is a fantastic overview of his session.


In the podcast, we focused on a definition Marc used for big data that focuses on six dimensions:


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