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Biztech Apr 3, 2012

The ABC Of Big Data

By Pranjal Kshirsagar
Rajesh Awasthi, Director – Telco and Cloud Business, NetApp India, shares with Biztech2.com some pointers on how companies can choose the right Big Data solution and use it to their best advantage.

How do companies perceive Big Data today?

Today Big Data’s perception is slightly different from what it earlier. Companies were used to it being a simple Business Intelligence or analytical solution. So, I would say, companies were always aware of Big Data, but now they are getting used to the new definition.

Now companies talk about databases with different types of data, viz. information, real-time data and information which is high fidelity and could be used for pattern discovery or context-aware intelligence.

Earlier, what companies could get from data collected over a period of time was more of hindsight information. Big Data goes beyond that and is fast becoming an insight and foresight tool which can enable a business to grow.

What would you term as the key drivers for deploying Big Data solutions?

Talking about the drivers for deploying Big Data solutions, the first would obviously be data growth. The second would be how you would operationalise the management of such data growth. The third and most critical would be, time-to-information – i.e. how would you deliver information in a timely manner.

How can companies decide what kind of Big Data solutions to go for?

The same solution cannot work for all verticals. How companies can go in for a best fit is looking at how solutions are classified.

They can be classified into three major areas which is the ‘ABC of Big Data’. Herein, ‘A’ stands for Analytics – the high performance analytical solutions; ‘B’ stands for Bandwidth – solutions which require high bandwidth; and ‘C’ stands for Content - high capacity solutions to manage the large content repository.

Type ‘A’ solutions are the traditional structured business analytics solutions, providing efficient analytics for extremely large datasets. An example could be tracking buying behaviour of a consumer in retail segment. BFSI and Telecom companies would also use this kind of solution to learn their customers’ usage patterns. Basically, companies which have high customer connect will deploy type ‘A’ solutions.

Type ‘B’ solutions help in obtaining better performance for extremely high workloads and are suited for companies that have the requirement of extremely high ingest rate performances. For instance, some countries have deployed solutions to identify typical behavioural patterns of miscreants from surveillance footage from busy areas such as airports, railways stations instead of doing a post-mortem of captured video after an undesirable event has occurred. This would require solutions which have the capacity to support full motion, hi-definition graphics along with the real-time information that is streaming in. Type ‘B’ solutions are a good fit here.

Type ‘C’ solutions have found their way into e-governance. A more recent example of its adoption is the UIDAI scheme. Here, the retinal scans and fingerprints of billions of people are being stored and data is being created in terms of petabytes. Type ‘C’ solutions would make these large data containers manageable.

Can you give a real life scenario of how enterprises can use Big Data solution to their best advantage?

I would like to cite here an example I recently read in A McKinsey report. This is an example of a retail chain which was tracking not only the sales from their own stores, but also integrated data from online buying portals and taking in feeds from social media sites. They created an analytical solution which used all this data and gave them foresight into what kind of products were in demand at what time of the year.

They integrated these insights into their supply chain system and kept those particular products well stocked for customers at the right time and the right price.

The point here is that enterprises can use Big Data solutions to get timely and more accurate information.

by Pranjal Kshirsagar

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