The Big Data seems to
be the buzz word not just in the bay area but almost everywhere. Big numbers
are interpreted as Big Data – which is true but not the whole truth. First, Big
data is not a recent phenomenon. Long before computers came into
the big picture, not many knew that there were ‘human computers’ that did
the math instrumental in launches of shuttles to space. Incredible! But that’s how an “all-women’
empowered team influenced science and technology with ‘mind’ math
to propel rockets, which today is accomplished with sophisticated
computers. The important connect – data. What the mind did then, a machine is
doing in the present.
Cave man didn’t really
drive cars, but they were the ones to invent the wheel and its that legacy we
have passed from generations to generations – from Ford to Ferrari to Tesla to
‘tomorrow’. The big deal – of course, the wheel.
This generation might
not know a ‘floppy disk’ could save 1.44 MB. Only that much? Ridiculously less.
Well, in its time, the floppy was an amazing storage device that can just fit
in your pocket and the bytes large enough for vital information.
Even before floppy, We did have tapes saving and storing data.
The world is enamored
with ‘big’. We have big screens, big tvs, big cars – everything bigger.
Dispelling the notion ‘small is big’, and again contrary to popular belief, it
was apple that set the pace and premise in building phones that were smarter
and ‘bigger’. And it would be apple that did roll out with smaller
screens and after the demise of Steve Jobs, there was a roll back and iPhone 6
and iPhone 6 Plus was launched with huge 5.5 inch screen – imposing in size
compared to its previous iPhone versions. Buyers clearly signaled that it isn’t
Steve but consumers’ diktat determine surge or slump in sales and clearly
the bet was on ‘big’.
‘Bigger is better’ –
and so went the line and sentiment. So when it comes to data, why and how the
Big Data became so prominent?
Pen and Paper
It sure dates before
old Star Trek episodes because by then we have seen computers
introducing itself to Captain Kirk “I am C-3PO, human/cyborg relations”. It’s
just an aside. On a serious note, the onset of the computer age was preceded by
man power – literally wherein things weren’t yet automated and mostly manual
with desk and file occupying key positions, and tap-tap-tap resonance of the
typewriter that somehow synced with the tick-tock of the clock. It will
be computer keyboard that silenced the sound with soft touches and
simplicity . Till the changeover, pen and paper were the ubiquitous
source to collect facts and figures which was processed as information.
Information is made up of data while the converse is not true. Just as
population grew, the data emanating also raised manifold that was raw and
refined. Then processing the data accrued proved to be a pain point as
screening quality data proved cumbersome weeding out the unnecessary and
unwanted. Well, how do you ascertain which is necessary? Probability and
Statistics became immensely popular a branch of applied mathematics
in employed heavily for data interpretation.
Data Storage and Data Processing
The challenge with the
burgeoning data posed a serious problem in storage. The memory of in-built
system storage expanded and mainframes were the rage. External storage like
floppy was superseded by external hard disk drives, compact discs , and
USB flash sticks with a greater capacity to hold data. Physical servers
to data centers were created in the growing demand and clamor to conserve data
and its integrity. We are talking of this moment of yottabyte computer. From
mega to peta to zeta to yota may not mean much other than ramping up the
storage size, till someone pitches the price, which is $100 trillion.
Image courtesy: www.gizmodo.com
The data storage will
be on-going struggle for memory and maintenance. Data warehouse grew big time
and along with came in Data Mining. One could mistake Data Mining as fishing
for data, rather Data Mining is about analyzing the worthiness of data and
extract it for required use.
With increased data at
disposal and companies unable to make head or tail, Data Analysts, and Data
Scientists introduced the intelligence aspects formally and Data Analytics was
clearly in the spotlight. So when massive data gets aggregated, the logistics
issues notwithstanding, consumers wanted information at ‘lighting speed’.
Not fast, but faster. If you are not up to it, you aren’t worth it. We have
Google , which holds 64% in market share as search, throwing
search results by the thousands.
54,002 Google searches
in 1 second.
It took us thus far to
get to the point? Well, a little bit of narrative hopefully should help to put
things in perspective. In this time and age, the consumer is well
informed and expectation is exponential. Search results don’t satisfy anymore –
it’s the accuracy in the results and the speed of delivery that’s decisive.
Intelligence inspires to probe ‘what’s next’. And expectation too hit the roof
“ok, now what?” questions the inquisitive customer. So the ability to preempt
and predict almost to the point of being prescient is typical ‘customer centric service’. Just like Hotels these days are able
to cater to the customer soon after check-in without any orders placed speaks
volumes of consumer behavior analysis in terms of taste and preference.
Likewise in search, the matching frequency to the ‘searched’ ought to be
mapped. You can’t afford to send your visitor or prospect or client to on a
wild-goose chase, and that’s slamming a lid hard on all the openings and
opportunities. Surprise with a ‘wow’ factor with customer exclaiming “God, look
at the speed and brilliance. It might even guess my next move and read my
mind.” Hence, it’s not the number of search results have gone up in
numbers, but the quality as well. Algorithms are amazing and fascinating
that are capable of meeting challenges like content, capture, curation,
analysis, search, delivery and ability to read patterns, choices,
preferences of the customer through lot many means like ‘last visited’ or ‘most
visited’ or page ranks or offering “you might like”.
We are In an era of
information overload. How do we make sense of this data? How do you separate
the wheat from the chaff? Contextual business data mining wherein data can be processed at superfast
speed hard to even imagine few years before. Entity that makes sense of information
overload and then converts into insights
to empower business. Well, that’s Big
Data.
Big Data, as part of
its evolution, will build a podium for posterity to offer improved and
increased services without saddling the end-user with any burden. It presents
quality data faster than expected with alarming accuracy that defies odds and
enhances your decision making. Informed Decisions.
In our subsequent posting, we will discuss more about Big Data and its impact in almost everything, yes, including sports.
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