Database Reference
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People also often talk about unstructured data, but, really, this just refers to
the format of the data. Could this be a reason we “suddenly” need big data?
We know that web data, especially web log data, is born in an unstructured
format and can be generated in significant quantities and volume. However,
is this really enough to be considered big data?
In my mind, the answer is no. No one property on its own is sufficient for
a project or a solution to be considered a big data solution. It's only when
you have a cunning blend of these ingredients that you get to bake a big data
cake.
This is in line with the Gartner definition of big data, which they updated
in Doug Laney's publication,
The Importance of Big Data: A Definition
(Gartner, 2012): “High volume, high velocity, and/or high variety
information assets that require new forms of processing to enable enhanced
decision making, insight discovery and process optimization.”
What we do know is that every CIO on the planet seems to want to start
a big data project right now. In a world of shrinking budgets, there is this
sudden desire to jump in with both feet into this world of big data and start
prospecting for golden nuggets. It's the gold rush all over again, and clearly
companies feel like they might miss out if they hesitate.
However, this is a picture that has been sharpening its focus for several
years. In the buildup to this ubiquitous acceptance of big data, we've been
blessed with plenty of industry terms and trends, web scale, new
programming paradigms of “code first,” and of course, to the total disgust
of data modelers everywhere, NoSQL. Technologies such as Cassandra and
MongoDB are certainly part of the broader ecosystem, but none have
resonated as strongly with the market as Hadoop and big data. Why? In
essence, unless you were Facebook, Google, Yahoo!, or Bing, issues like web
scale really didn't apply.
It seems as though everyone is now building analytics platforms, and that,
to be the king of geek chic, requires a degree in advanced statistics. The
reason? Big data projects aren't defined by having big data sets. They are
shaped by big ideas, by big questions, and by big opportunities. Big data is
not about one technology or even one platform. It's so much more than that:
It's a mindset and a movement.
Big data, therefore, is a term that underpins a raft of technologies (including
the various Hadoop projects, NoSQL offerings, and even MPP Database
