Comments on: Big data: The quick and the dead http://gigaom.com/2012/05/13/big-data-the-quick-and-the-dead/ Wed, 19 Jun 2013 18:07:48 +0000 hourly 1 http://wordpress.com/ By: Sarunas Chomentauskas http://gigaom.com/2012/05/13/big-data-the-quick-and-the-dead/#comment-868656 Wed, 25 Jul 2012 18:46:25 +0000 http://gigaom.com/?p=520606#comment-868656 One more false premise in this article is ‘more is not better’ when it comes to data. In fact, the opposite is true. Relatively simple math is unreasonably effective given sufficiently large data sets: a big data fact that is true, and on which the entire google edifice is founded.

]]> By: Tim Hoolihan http://gigaom.com/2012/05/13/big-data-the-quick-and-the-dead/#comment-841630 Wed, 16 May 2012 16:48:08 +0000 http://gigaom.com/?p=520606#comment-841630 The article is based on a couple of premises that aren’t true: users have all their data available in a relational warehouse, and that analytics is the only use of Hadoop. Hadoop allows interrogation of disparate data sources in a way not possible with traditional BI tools. Agreed, you should be using those tools where possible, but just because traditional BI on a warehouse is easier doesn’t mean that it’s answering the questions that are most valuable. A great example of this is social media data, that storing locally is usually against the terms of the social network. You have to use a tool like Hadoop to do large scale queries involving internal and social data.

In addition, there are lots of other uses of Hadoop. Lots of people are moving to different architectures where transactions are stored in their rawest form in a simple redundant database and Hadoop is used to present relational views of historical data, and queries are run over realtime and the historical sources. That massively reduces writes, allowing greater scaling and simplicity. For a better description of this architecture, check out the Pragmatic Programmers Big Data book currently in Beta.

There may be a bit of a goldrush mentality around this technology, and some of it is overblown. But it is a flexible tool that has more uses than you are describing, and solves real problems that many firms are having.

]]> By: Mark Zohar http://gigaom.com/2012/05/13/big-data-the-quick-and-the-dead/#comment-841450 Tue, 15 May 2012 22:46:36 +0000 http://gigaom.com/?p=520606#comment-841450 Great article. At TrendSpottr (http://trendspottr.com), we very much believe that one of the most disruptive Big Data opportunities is real-time analysis of small data. More specifically, our focus is on identifying trends and predictive insights from small data sets that reside within Big Data streams; i.e, a predictive early warning system based on real-time pattern recognition and statistical analysis. The reality, as you note, is that most of the data within Big Data is either dormant or dead. By focusing on only those data elements that provide the potential for insight and action, we can leverage Big Data by starting small.

]]> By: H.M. http://gigaom.com/2012/05/13/big-data-the-quick-and-the-dead/#comment-841296 Tue, 15 May 2012 10:19:14 +0000 http://gigaom.com/?p=520606#comment-841296 Nice article Fred! I think it is worth mentioning HPCC Systems open source offering provides a single platform that is easy to install, manage and code too. Their built-in analytics libraries for Machine Learning and integrations tools with Pentaho for great BI capabilities make it easy for data analysts to work with Big Data. I believe HPCC is better than Hadoop and commercial offerings, it has a real-time data analytics and delivery engine (Roxie) and runs on the Amazon cloud like a charm through the One Click portal. For more info visit: hpccsystems.com

]]> By: @dataElGrande http://gigaom.com/2012/05/13/big-data-the-quick-and-the-dead/#comment-841127 Mon, 14 May 2012 17:52:23 +0000 http://gigaom.com/?p=520606#comment-841127 Although this is a thoughtful article, one must ponder over the question “How can I be sure the dormant data I have won’t bring me useful insights?” without actually going through the process of trying big data analytics. It’s the possibility of improvement that is driving companies towards powerful reporting and analytics, not so much their “fear of underutilizing data.” If interested, check out the helpful tools Pentaho has to offer dealing with Big Data Reporting

http://www.pentaho.com/big-data/

]]> By: Stavros http://gigaom.com/2012/05/13/big-data-the-quick-and-the-dead/#comment-841061 Mon, 14 May 2012 12:20:12 +0000 http://gigaom.com/?p=520606#comment-841061 Great article. Large quantities on internal data is one thing, however, when analyzing vast amounts of internal and external data in real time, simple analytics won’t do by design. Like all other technologies, Big Data stack will evolve overtime and will become standard with more off the shelf tools.

]]> By: database support http://gigaom.com/2012/05/13/big-data-the-quick-and-the-dead/#comment-841048 Mon, 14 May 2012 09:47:46 +0000 http://gigaom.com/?p=520606#comment-841048 nicely written and self explanatory

]]> By: Keith Bolam http://gigaom.com/2012/05/13/big-data-the-quick-and-the-dead/#comment-841047 Mon, 14 May 2012 09:24:35 +0000 http://gigaom.com/?p=520606#comment-841047 Excellent thoughts that everyone should take head of.

]]> By: thescarletnumbers http://gigaom.com/2012/05/13/big-data-the-quick-and-the-dead/#comment-841045 Mon, 14 May 2012 09:20:58 +0000 http://gigaom.com/?p=520606#comment-841045 As always Gigaom hits the nail straight on the head. This is extremely well written and very useful to anyone curious about the relevance and value of big data.

]]> By: NetBinge http://gigaom.com/2012/05/13/big-data-the-quick-and-the-dead/#comment-841034 Mon, 14 May 2012 07:17:52 +0000 http://gigaom.com/?p=520606#comment-841034 SolveOut.com is FOR SALE NOW at NetBinge.com

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