The Four V's of Big Data

Big Data describes a type of enormous data in volume and is always expanding exponentially as a factor of time. This type of data is quite large and complex that the usual data processing tools can neither process it nor store it. In essence, Big Data is the type of data in large quantities. Since Big Data differs from the traditional type of data, it is characterized differently for the purpose of simplicity and clarity. These features of Big Data are mostly termed as the Four V’s of Big Data. In other words, they are special attributes, which highlight the features of Big Data. These features are volume, veracity, velocity, and variety. Each of these characteristics is discussed below.

Volume

Volume defines the main feature of Big Data. It has no minimum storage capacity as the data exponentially grows all the time. The size of data needs special processing techniques as the existing tools are not capable of providing the desired analysis. Therefore, regular personal computers are not adequate enough to run such resource-consuming processes. A simple example of Bid Data is the card transactions all around the world within a single day.

Veracity

Veracity defines data quality. High veracity refers to a data set that possesses all the necessary data points for effective analysis so as to create meaningful results. An excellent instance of high veracity is the data-driven from a simulated accident at a car crash site. Conversely, low veracity data refers to a data set with low data points or data that contain few meaningful (usable) data. In this case, data is filled with noise. Low veracity data is usually derived from processes that are spontaneous and lack any form of control.

Velocity

The velocity feature defines the speed of data processing. This feature is essential, especially when considering the large amount of data that comes in every second on the internet. For example, the number of new posts that appear on a single social media platform is of significantly high velocity. The velocity of data is critical to streaming services, as many people demand access.

Variety

The variety of data is an important feature. Variety basically refers to the structure of a data set, which can include time, quality, and date. These variables are easily structured on a typical relational database system. However, the variety gets a little complicated when there isn’t a defined structure. The pictures or videos posted on a social media platform, x-ray images, and more are all images that can be taken and store. However, these sets of data do not possess a well-defined model. As a result, this makes the handling of unstructured data fundamental to Big Data analysis. As a result of the complexities presented by unstructured data, it is best analyzed by associating it with structured data. Nonetheless, this process is still lacking. Therefore, one of the critical objectives of Big Data is to provide a comprehensive way of understanding unstructured data.

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