|By Jnan Dash||
|September 10, 2012 04:30 AM EDT||
With every passing day, Big Data assumes new strength as a significant force in our industry. Someone even said that Big Data is transforming business same way IT did few decades ago.
The overall revenue (includes hardware, software, service) for Big Data is said to be around $5.1B in 2011 and includes players such as IBM, Intel, HP, Fujitsu, etc. This is hard to fathom! But pure-play revenue coming from players such as Vertica, Aster, Cloudera, Greenplum, 1010Data, etc. is valued at $468M in 2011. Then someone said the projected revenue from Big Data will reach an astounding $53B by 2017 (source- Wikibon), growing to $10B in 2013, $32 in 2015 and $48B in 2016. We can argue on these numbers, but let us agree that this will be quite big. Why is that?
We all know about data growth. Facebook with 900M users in April, 2012 did analytics on 25PB (petabytes) of compressed data ($125PB of raw data). Twitter handled 400M tweets a day during June 2012. Overall corporate data is supposed to grow by 94% year to year. Facebook made several shifts – from “what data to store” to “what can we do with more data”. They simplified data analytics for end users by adopting more than one infrastructure to solve all Big Data problems.
I read that someone identified the 3 I’s of Big Data besides the 3 V’s (volume, velocity, and variability). They are Immediate (do something now), Intimidating (what if I don’t?), and Ill-defined (what is it anyway? many definitions). The middle one “Intimidating” refers to leveraging Big Data applications like online advertising and marketing optimization, or applications to predict crime data, or machine-generated data for analytics.
Many vertical industries are trying to exploit Big Data and analytics – retail (today’s recommendation), sales leads (campaign recommendation), IT (from manual log files to operational intelligence), customer service (customer insight), billing (intelligent coding), fraud management (social profiles), and automatic operations management.
Key challenges remain, specially in the areas of visual analytic tools, and doing trend analysis across multiple data sources. But several new start-ups are addressing these white spaces. Big data is not just Hadoop or NoSQL database systems. It encompasses current RDBMS data and new unstructured data plus all the analytics and special applications to provide businesses the insight for better growth.-
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Between 2005 and 2020, data volumes will grow by a factor of 300 – enough data to stack CDs from the earth to the moon 162 times. This has come to be known as the ‘big data’ phenomenon. Unfortunately, traditional approaches to handling, storing and analyzing data aren’t adequate at this scale: they’re too costly, slow and physically cumbersome to keep up. Fortunately, in response a new breed of technology has emerged that is cheaper, faster and more scalable. Yet, in meeting these new needs they...
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