Big Data is claimed as a collection of data sets so large that they are difficult to process using conventional data processing techniques. Based on the prevailing trends, Big Data is set to become an integral part of every organization. Big Data basically has 3 characteristics which provide us with its nature and framework.
Why to crunch the Data
Is Big Data Analytics helpful? Dealing with Big Data using conventional methodologies would pose a challenging task and result in waste of resources as well as time. To deal with this, organizations need to find the right mix of expertise and analytics techniques. Big data analytics enables organizations to analyze a mix of structured, semi-structured and unstructured data in search of valuable business information and insights. It would help the organization to gain valuable knowledge about the large volume of data that cannot be assessed with the traditional analytics.
Volume
This deals with the size aspect of Big Data. With the exponential increase in the amount of data generated due to a surge in global connectivity, it is a challenging task to store and process data with the traditional database systems.
Velocity
This refers to the speed at which data is processed to meet the sudden increase in demand. Organizations are expected to process the data and share it with the respective businesses for smooth functioning of day-to-day activities.
Variety
Big Data arrives from a diverse set of data being shared over the digital medium. With this diversity, it is important to classify the data according to its specifications. This is not possible with the conventional methods in hand.
Veracity
The quality of the data being captured can vary greatly depending on various factors. Accuracy of analysis depends on the veracity of the source data.
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