The life cycle of Big Data

Many organizations are considering Big Data as not only just a buzzword, but a smart system to improve business and get relevant marked information and insights. Big Data is a term that refers to managing huge amounts of complex unprocessed data from diverse sources like databases, social media, images, sensor-driven equipment, log files, human sentiments, and so on. This data can be in a structured, semi-structured, or unstructured form. Thus, to process this data, Big Data tools are used to analyze, which is a difficult and time-intensive process using traditional processing procedures.

The life cycle of Big Data can be segmented into Volume, Variety, Velocity, and Veracity--commonly known as the FOUR V's OF BIG DATA. Let's look at them quickly and then move on to the four phases of the Big Data life cycle, that is, collecting data, storing data, analyzing data, and governing data.

The following illustrates a few real-world scenarios, which gives us a much better understanding of the four Vs defining Big Data: