Moving data to compute or compute to data? That is the Big Data question

Dorky attempts at geek Shakespere aside; as the volume, complexity, and variability of your data systems increase in … entropy …, this becomes a fundamental question in whether one scales up or scale out their data problem. Apologies for the nerdy chemistry references in advance – which starts with this picture of Dr. Arthur Grosser (more later) As noted in the previous post Scale Up or Scale Out your Data Problems? A Space Analogy, the decision to scaling up or scaling out your data problem is a key facet in your Big Data problem.  But just as important as the…

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Scale Up or Scale Out your Data Problems? A Space Analogy

As I am writing more about Big Data, I’m been asked whether we need to have traditional relational or cube systems now that we have Big Data / NoSQL / Hadoop.  My responses are to note that these are different systems that serve different purposes even though both are used to better understand data. But before we dive into the specifics surrounding relational databases compared to Hadoop / Big Data, we need to first talk about the differences between solving the a data problem by scaling up the problem or scaling it out. One way to understand the difference is…

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Travel Tuesday: Top 5 reasons to go to Costco in Taiwan (from a US expat)

. . . I love Pittsburgh, they put fries on nachos here. — Pete Lattimer, Warehouse 13 . . . For those un-familar with the reference, Warehouse 13 is an awesome Syfy show…and Costco is a warehouse store – yeah, weak connection here. Yet another themed blog series Starting with the recent Foodie Friday blog post (Foodie Friday: Taiwanese dessert 芋圓), figured I should add another non-geek themed blog post series – Travel Tuesday – probably every week or two, eh?! Okay…so what’s this about Costco? yeah right – so back to the title of this post – what are…

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It’s all about the little things…on the inside!

  For some people, small, beautiful events is what life is all about! — Doctor Who: Earthshock, Peter Davison as the 5th Doctor (Story 122)             A tad off course, but today, I was just wow’ed by my Apple Magic Touch mouse. Why do you ask? Because of the beauty of industrial design and the wonderful merge of function and form.  The mouse itself is quite sleek and low profile and I like using the multi-gesture swipes all within the the comfort of a few finger moves.   But the thing that got my attention…

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The aggressive optimism of Hadoop

  Aggressive optimism and a no enemies policy pays dividends — Eric14 aka Eric Baldeschwieler (@jeric14) during ApacheCon 2011 North America Thursday Keynote.     After all of these years doing BI, why have I jumped on the bandwagon of Hadoop and Big Data? Well, if you read some of my previous blog posts like Revelations – rolling the Hard Six to SQL BI and Hadoop or At a Crossroads … from SSAS to BigData! – I never left the Big Data wagon in the first place. Whether it is Tier-1 BI, web analytics, or Big Data – it’s all…

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You know that I’m tired when…

Sorry that I haven’t blogged in awhile, but there’s lots of interesting things happening these days all in prep for the SQLPASS summit, eh?!  It’s been long nights and lots of fun chaos! Saying this, you know that I’m tired when… you’re getting <3h of sleep / night you’re running all of your team meetings via conference calls from your car you walk into a customer executive briefing wearing shorts realized my Mandarin Chinese is so bad that I’m learning new words while watching “Ni Hao, Kai Lan” was actively thinking about joining sales was losing a real debate with…

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The potential of Big Data

To better understand the excitement around Big Data, there is an informative  report by McKinsey Global Institute – Big data: The next frontier for innovation, competition, and productivity.   I encourage you to read this report and there are some key call outs that showcase the potential of Big Data.   Big Data call outs! It’s about the next wave of jobs with the main domains of Big Data being Healthcare, Public Sector, Retail, Manufacturing, and Telecommunications. 140,000-190,000 more deep analytical talent positions and 1.5 million more data-savvy managers needed to take full advantage of big data in the United States…

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