What are the different features of big data analytics
Features of big data analytics are-
The pace at which data is processed is referred to as velocity. Any large data process's performance depends on its ability to move at a high rate. The velocity of change, activity bursts, and the connecting of incoming data sets are all part of it.
The volume of data or its size is another important feature of big data. Generally, big data volume approaches Gigabytes, Zettabytes (ZB), and Yottabytes (YB). It is expected to rise further in the near future as more and more data is getting generated at exponential rates.
The value of big data from profit or importance point of view is another important feature of it. It is a measure of how important the data is for an organization and what value it will add to the organization’s profits.
Variety refers to the various types of data that may be got from different sources. The variety of data should be clearly determined and organized well as this may directly affect the value derived from it.
Veracity refers to the accuracy of the data gathered. This is very important as big data is used further to draw inferences that will affect the business decisions.
This refers to how valid the big data is. It also refers to its relevance for the purposes it is gathered for.
Big data constantly changes with time. So volatility or variability of data with time is another off its feature.
Another feature of big data is visualizations. Data is understood through different visualizations like charts and graphs that makes it easier to interpret and draw insights from.
Learn more about Big Data and its applications from the Data Engineer Training.