Big Data

Every activity on a cable or airway creates a digital trail that leaves behind – DATA. Unimaginable amounts of data are being generated every minute every day, so much so that it can’t be allowed to just disappear. Not when patterns exist among this data. Not when predictive insights can be gained from this data. Have a look at the bulk of data created every minute on some of the popular websites.

Big Data is just that – data which is big enough to make it difficult to handle. Innovations in storing, organizing and interpreting are needed to have an advantage out of this data. Existing systems and structures can’t cope with Big Data. For one, existing Information Systems are created to deal with organized data, rendered through relational databases. Big Data plays with unorganized and unstructured data. But Big Data goes beyond mere data structures. It is different because there is no idea about the type of data that is coming through. Or when will it be generated. It is different because of the way in which the data is accumulated in the first place. Think of Facebook. Think of the millions of bytes of data generated every minute – what gets posted, what gets shared, who is sharing, which apps are being accessed, where, by whom and so on. Big Data is unique and powerful because of the Volume, Velocity and Variety of data.

Lets talk volume first – nearly 3 exabytes of new data are generated every day. An exabyte is 1 billion GB (gigabyte). With a horde of music and movies, I still haven’t managed to get the better of my 500 GB hard disk. So now you know what kind of gigantic volume of data needs to be tackled. And handling ‘large’ volume of data is the least significant of Big Data’s capabilities.

Everything from a POS transaction to a frustrated customer’s post on FB, Big Data is competent to track, assimilate and organize from a variety of data sources and data types – documents, web logs, images, strings, etc.

You must have at many times been flabbergasted by the inability of processing technology (computers, phones, anything) to keep up with your requirements to work across multiple application software. And this too, when your device has to manage seemingly predictable data. Keeping up with the volume and the variety of data is the most important characteristic of Big Data – the speed at which it does what it is supposed to do – Velocity of converting data into value. This is where business analytics is really interested in – near to real time data accumulation, interpretation and subsequent action.

I am Ravi Vaidya, a management educator by profession. This is where I intend to be myself, where I can ‘I’deate.

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