BACHELOR OF BUSINESS ADMINISTRATION

Detailed explanation-1: -What is Veracity in Big Data? Veracity is a big data characteristic related to consistency, accuracy, quality, and trustworthiness. Data veracity refers to the biasedness, noise, abnormality in data. It also refers to incomplete data or the presence of errors, outliers, and missing values.

Detailed explanation-2: -An example of a high veracity data set would be data from a medical experiment or trial. Data that is high volume, high velocity and high variety must be processed with advanced tools (analytics and algorithms) to reveal meaningful information.

Detailed explanation-3: -Data veracity, in general, is how accurate or truthful a data set may be. In the context of big data, however, it takes on a bit more meaning. More specifically, when it comes to the accuracy of big data, it’s not just the quality of the data itself but how trustworthy the data source, type, and processing of it is.

Detailed explanation-4: -Big Data Veracity refers to the biases, noise and abnormality in data. Is the data that is being stored, and mined meaningful to the problem being analyzed. Inderpal feel veracity in data analysis is the biggest challenge when compares to things like volume and velocity.