Six disruptive possibilities from big data
Specific ways big data will inundate vendors
and customers.
My new book, Disruptive Possibilities: How Big
Data Changes Everything, is derived directly from my
experience as a performance and platform architect in the old enterprise world
and the new, Internet-scale world.
I pre-date the Hadoop crew at Yahoo!, but I intimately understood
the grid engineering that made Hadoop possible.
For years, the
working title of this book was The
Art and Craft of Platform Engineering, and when I started working
on Hadoop after a stint in the Red Hat kernel group, many of the ideas that
were jammed into my head, going back to my experience with early
supercomputers, all seem to make perfect sense for Hadoop.
This is why I frequently refer
to big data as “commercial supercomputing.”
In Disruptive Possibilities,
I discuss the implications of the big data ecosystem over the next few years.
These implications
will inundate vendors and customers in a number of ways, including:
1.
The disruption to the silo mentality, both in IT organizations
and the industry that serves them, will be the big story of big data.
2.
The IT industry will be battered by the new technology of big
data because many of the products that pre-date Hadoop are laughably
unaffordable at scale.
Big data hardware and software is hundreds of times faster than
existing enterprise-scale products and often thousands of times cheaper.
3.
Technology as new and disruptive as big data is often resisted
by IT organizations because their corporate mandate requires them to obsess
about minimizing OPEX and
not tolerate innovation, forcing IT to be the big bad wolf of big data.
4.
IT organizations will be affected by the generation that
replaces those who invested their careers in Oracle, Microsoft, and EMC.
The old adage “no one
ever gets fired for buying (historically) IBM” only applies to mature,
established technology, not to immature and disruptive technology.
Big data is the most
disruptive force this industry has seen since the introduction of the
relational database.
5.
Big data requires data scientists and programmers to develop a
better understanding of how the data flows underneath them, including an
introduction (or reintroduction) to the computing platform that makes it
possible.
This may be outside of their comfort zones if they are similarly
entrenched within silos.
Professionals willing to learn new ways of
collaborating, working, and thinking will prosper.
That prosperity will be
as much about highly efficient and small teams of people as it is about highly
efficient and large groups of servers.
6.
Civil liberties and privacy will be compromised as technology
improvements make it affordable for any organization (private, public or
clandestine) to analyze the patterns of data and behavior of anyone who uses a
mobile phone.
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