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In many cases, the end of the year gives you time to step back and take stock of the last 12 months. This is when many of us take a hard look at what worked and what did not, complete performance reviews, and formulate plans for the coming year. For me, it is all of those things plus a time when I u...
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Big Data – Business Value
With every passing day, Big Data assumes new strength

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.-

Read the original blog entry...

About Jnan Dash
Jnan Dash is Senior Advisor at EZShield Inc., Advisor at ScaleDB and Board Member at Compassites Software Solutions. He has lived in Silicon Valley since 1979. Formerly he was the Chief Strategy Officer (Consulting) at Curl Inc., before which he spent ten years at Oracle Corporation and was the Group Vice President, Systems Architecture and Technology till 2002. He was responsible for setting Oracle's core database and application server product directions and interacted with customers worldwide in translating future needs to product plans. Before that he spent 16 years at IBM. He blogs at http://jnandash.ulitzer.com.

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