volume,variety and velocity

Blog 2: Volume, Variety and Velocity

It is studied that the dimensions of big data include three defining properties, which are volume, variety and velocity. Volume expresses the amount of data, variety explains about the number of data types processed and velocity is about the speed of data processing. As per the 3Vs model, the issues of big data management generates from the expansion of 3Vs. On the other hand, it is identified that the volume of data determines the data sets’ size which required to be analysed and processed that may now be frequently bigger in comparison to petabytes and terabytes (Hofmann, 2017). In addition, the sheer volume of data needs diverse processing tools as against traditional storage and processing capabilities. It indicates that the data sets in big data can be significantly large for processing data with a regular desktop or laptop processor. It is considered crucial to assess the amount of data before processing in order to ensure relevancy of the data. 

Velocity, on the other side, expresses the speed with which data is obtained. It is regarded important to have a distinct processing technique in order to generate a high velocity data. Facebook posts and Twitter messages are considered as one of the examples of the data which is produced with high velocity. Big data has the capacity to accept the huge inflow of data and can process data in quick pace, which also helps in avoiding bottlenecks in the process of data (Sheth, 2014). Apart from that, variety in big data explains all the unstructured and structured data, which has the possibility of getting generated either by machines or humans. The variety in data types needs distinctive processing capabilities and specialist algorithms on a regular basis. CCTV audio and video documents which are obtained at different regions are considered as the example of high variety data sets.