Tuesday, May 24, 2016

The 'Big' Data

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.


 Big Data
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.

Thank you for stopping by and spending your time reading this blog.  

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