Traditionally, the OLTP systems processed transaction data in relational databases and OLAP systems provided analytics on data in multi-dimensional data stores. This is all fine when the amount (volume) of data is in the range of Terabytes, when the rate (velocity) at which data grows is linear and when the types of data (variety) to be dealt with is limited and structured. By the way, Volume, Velocity and Variety are often referred to as the 3Vs of data.
But a few things are changing rapidly. The 3Vs are increasing dramatically in certain cases such as Social Media. Such data, typically, will have the following characteristics –
Huge amount
Rapid unplanned growth
Unstructured data types (Photos, videos, text, graph etc)
This is the BIG DATA problem!
How do we leverage this in the context of an enterprise? From my experience, in two clear ways.
What if we could pull large amounts of data that is essentially unstructured into a central infrastructure and were able to –
1. Identify relationships among the data items from different sources.
It would open up several new possibilities of leveraging the relationships. A Private Bank dealing with its high net worth clients can analyze the relationships among key data items available in Social media on their clients and position new products of interest to those clients.
2. Identify patterns and trends.
It would help predict future events. A retail store would be able to look at unstructured data from various sources and predict the buying pattern of its clients with a certain profile.
There are surely many more ways of leveraging big data. Look forward to seeing your views.
Businesses have to do something different with what they already have and what is out there in an unstructured manner in the open. Can they look at it differently to generate new opportunities ? That, in my view, is the promise of Big Data!