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May 30, 2012

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Brian Gracely

After reading Dave McCrory's original posts on Data Gravity:
http://blog.mccrory.me/2010/12/07/data-gravity-in-the-clouds/
http://blog.mccrory.me/2011/04/02/defying-data-gravity/

I wrote about the concept of Planet Data a few months ago http://www.cloudsofchange.com/2012/02/welcome-to-planet-data.html

and we spoke with Dave about the evolution of Data Gravity thinking on the podcast last week: http://www.thecloudcast.net/2012/05/cloudcast-eps38-project-razor-google.html

Once we understand the impact (challenges of data movement), we can also begin to understand the opportunities unlocked by beginning to create APIs around large amount of valuable data that could unlock new potential for customer, partners, researchers - http://www.thecloudcast.net/2012/02/cloudcast-eps32-apis-new-language-of.html

Branden Williams

Hey Chuck! With respect to the library, I think you are hitting on something that drives me nuts about educational institutions--they are terrible at marketing! And to think, all they would have to do is throw an "e" in front of that Library name and it would make sense.

The Library, in its traditional sense, is where my son gets books for his weekly reading and where we take the kids to get books during the summer.

In my case, my university library is both a Single Sign-On (SSO) login that gets me electronic access to those same gravity wells you describe and a collection of links to external data sources for use in research. Albeit, most of the linked data sources are public, which I think is more to your point. When will valuable data sets be available for better analysis?

BRCDbreams

Chuck,

There is an interesting post by Nicolas Carr on the noise vs signal aspects of data.

http://www.roughtype.com/archives/2012/05/a_little_more_s.php

The observation is more frequent measurements increase the noise level, not the signal. If data sets are big because they have more frequent measurements, you may find it a lot harder to understand the data than if the data samples are taken less frequently. Or, to continue with the "gravity" metaphor, if you collect too much data, your get so much gravity, you end up with a black hole from which nothing escapes, including information.

In the end, businesses need to keep cost in mind. The fact you can sample data every second may increase the cost of actually understanding the data.

Interesting ...

Chuck Hollis

Hi

As I work with data science professionals and similar researchers, they seem to be much more interested in correlating disparate data sources vs. simply more data from the same source.

I suspect that Nick's observations wouldn't apply if that's the case.

-- Chuck

Scott Lee

Jer Thorpe gave a TEDx talk recently about the weight of data. he comes at it from a visualizer's perspective - how to get a different kind of worth from the information. worth a few minutes to check out: http://www.youtube.com/watch?v=Q9wcvFkWpsM

Chuck Hollis

Scott

Fascinating story. Well worth the time to watch. Thanks for sharing!

-- Chuck

ティンバーランド ブーツ

毎年、このシーズンは旅行に最適な時期です。ティンバーランド スニーカー、はあなたたちの屋外スポーツの欲求と、“軽装に行く”と“ドライ付随する”シリーズの機能性とファションの仕立てミックスの追求を満たすように設計しています。

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Chuck Hollis


  • Chuck Hollis
    Chief Strategist, VMware Storage and Availability Business Unit
    @chuckhollis

    Chuck works for VMware, and is deeply embroiled in all things software-defined storage these days.

    Previously, he was with EMC for 18 years, most of them great.

    He enjoys speaking to customer and industry audiences about a variety of technology topics, and -- of course -- enjoys blogging.

    Chuck lives in Holliston, MA with his wife, three kids and four dogs when he's not traveling. In his spare time, Chuck is working on his second career as an aging rock musician.

    Warning: do not buy him a drink when there is a piano nearby.
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