MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Veracity is a big data characteristic related to consistency, accuracy, quality, and trustworthiness. Data veracity refers to the biasedness, noise, abnormality in data.

Detailed explanation-2: -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.

Detailed explanation-3: -Veracity is the fourth V in the 5 V’s of big data. It refers to the quality and accuracy of data. Gathered data could have missing pieces, may be inaccurate or may not be able to provide real, valuable insight. Veracity, overall, refers to the level of trust there is in the collected data.

Detailed explanation-4: -Veracity refers to the degree of accuracy in data sets and how trustworthy they are. Raw data collected from various sources can cause data quality issues that may be difficult to pinpoint.

Detailed explanation-5: -The variety in data types frequently requires distinct processing capabilities and specialist algorithms. An example of high variety data sets would be the CCTV audio and video files that are generated at various locations in a city. Veracity refers to the quality of the data that is being analyzed.