The term 'Big Data' describes a vast amount of data, or chat, generated from two main sources: people and computers. People spend a lot of time talking on social networks like Twitter and Facebook and producing on-line content about their companies, affiliated organisations and themselves. Computers and devices, now IP enabled and connected to the internet, now have the ability to send their instrumentation information into internet. The latter phenomenon is known as 'the internet of things': a description of how connected devices and sensors, from shoes to thermostats to cloud server farms, now have a voice and can make information about how they are used and what they experience accessible to data crunching algorithms. These algorithms would then produce insights that can be feed back into the real world and affect everything ranging from peoples behaviour to how corporations are run.
Handling all this data is a massive computational challenge. Compounding the challenge is that data is growing exponentially, may be stored over the place and even kept in different formats. To address these challenges two key technologies have evolved to help us along: MapReduce and NoSQL.
But before we delve into these let's break down the attributes of Big Data into a bit more detail.
