Services like social networks, web analytics, and intelligent e-commerce often need to manage data at a scale too big for a traditional database. Complexity increases with scope, scale and demand, and handling big data is not as simple as just doubling or increasing down on your RDBMS or rolling out some trendy new technology. Fortunately, scalability and simplicity are not mutually exclusive—you just need to take a different approach. Big data systems use many machines working in parallel to store and process data, which introduces fundamental challenges unfamiliar to most developers.
Big Data tells you to build these systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data(for example Apache Hadoop). It describes a scalable, easy to understand approach to big data systems that can be built and run by a small team.
for more details :
http://www.mckinsey.com/insights/mgi/research/technology_and_innovation/big_data_the_next_frontier_for_innovation
