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Forrester's Liz Herbert speaking at the Big Data Round table. Other speakers (from left) Shailendra Ravi of EMC, Ravindra Krishnappa and Saurabh Suri of UST Global ( IndiaTechOnline photo)
 
 
BIG data = Big opportunity: UST roundtable

Bangalore May 8 2012: IT Enterprise leaders, led by analysts, Forrester, suggested on Monday, that the big new opportunity, in India, might be Big Data -- industry buzzword for vast amounts of mostly unstructured data that defies conventional methods for managing them.
Liz Herbert, Principal Analyst at Forrester serving Sourcing & Vendor Management professionals who steered a round table discussion, suggested four ‘V’s volume, velocity, variability and variety which would determine if the data within an enterprise was ripe for Big Data treatment. “Big Data also needs to be clean data”, she added, “ having built the business case for Big Data, it is time to ‘clean it up’, build a dedicated team to address the challenge ( with a sprinkling of data scientists not just IT guys) – then pick the right technology”.
While there is no one view on how big one’s data needs to be to get the “Big” tag, Shailendra Ravi, Senior Director, Global Services, EMC, said 100 Terabytes was a ball park number – as long as the data approximately doubled every year. Twitter with 100 million users and Facebook with 800 million were among the major drivers of big data – but ironically, it was not all about size. Even a few gigabytes of data – the size of an average PC hard drive, could need a Big Data approach if its deployment or harnessing poses problems.
“C2C may have a new meaning in the BBig Data contest”, said Ravindra Krishnappa, angel investor and Big Data expert, “ It is now Conversation to Conversation”.
Saurabh Suri, Senior Director, Solutions & Services, Big Data & Predictive Analytics at UST said the biggest markets in India for Big Data Analytics would be government, B2C and Financial sectors.

Tech Note: What is Big Data – multiple views
Techtarget.com
: Big data (also spelled Big Data) is a general term used to describe the voluminous amount of unstructured and semi-structured data a company creates -- data that would take too much time and cost too much money to load into a relational database for analysis. Although Big data doesn't refer to any specific quantity, the term is often used when speaking about petabytes and exabytes of data.
Wikipedia: Big data is a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target currently ranging from a few dozen terabytes to many petabytes of data in a single data set.
One current feature of big data is the difficulty working with it using relational databases and desktop statistics/visualization packages, requiring instead "massively parallel software running on tens, hundreds, or even thousands of servers".The size of "big data" varies depending on the capabilities of the organization managing the set. "For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration."
IBM:What is big data?Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data.
The 2011 Digital University Study (IDC): http://www.emc.com/collateral/demos/microsites/emc-digital-universe-2011/index.htm  
What is "Big Data" -- and just how big is it anyway? Patricia Florissi, EMC's CTO for the Americas, narrates this fun explanation of why we all need to think "Big" about "Big Data" http://www.youtube.com/watch?v=eEpxN0htRKI ( see our Tech Video spot for a few days).