Why is Big Data different from any other data that we have dealt with in the past? There are 'four V’s' that characterize this data: Volume, Velocity, Variety, and Veracity.
Volume refers to the amount of data available to analyse
Velocity refers to the speed with which the data is generated
Variety refers to the diversity of data sources and types of data points captured
Veracity refers to the quality of data being analysed.
Read in detail about the four Vs of Big data
An innovation that creates a new value network and market, and disrupts an existing market and value network by displacing the leading, highly established alliances, products and firms is known as Disruptive Innovation. Clayton M. Christensen and his coworkers defined and analysed this phenomenon in the year 1995. But, every revolutionary innovation is not disruptive. When a revolution creates a disorder in the current marketplace, then only it is considered as disruptive.
The term ‘disruptive innovation’ has been very popular over the past few years. In spite of many differences in application, many agree on the following.
Disruptive innovations are:
More accessible (with respect to distribution or usability)
Cheaper (from a customer perspective)
And utilise a business model with structural cost advantages (with respect to existing solutions)
The disruptive innovation coming from big data are big data analytics processes and technologies.
For organisations, big data is a disruptive force. It means that people require more than new skills, technologies and tools. They need an open mind to rethink about the decision-making processes they have followed for a long time and transform the way they operate.
However, it is not particularly easy to force this type of change in a big and diverse organisation. Knowing how to introduce data-driven culture can be a starting point.
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