Big Data

Volume – Volume represents the volume i.e. amount of data that is growing at a high rate i.e. data volume in Petabytes
Velocity – Velocity is the rate at which data grows. Social media contributes a major role in the velocity of growing data.
Variety – Variety refers to the different data types i.e. various data formats like text, audios, videos, etc.
Veracity – Veracity refers to the uncertainty of available data. Veracity arises due to the high volume of data that brings incompleteness and inconsistency.
Value –Value refers to turning data into value. By turning accessed big data into values, businesses may generate revenue.

HDFS runs on a cluster of machines while NAS runs on an individual machine. Hence, data redundancy is a common issue in HDFS. On the contrary, the replication protocol is different in case of NAS. Thus the chances of data redundancy are much less.
Data is stored as data blocks in local drives in case of HDFS. In case of NAS, it is stored in dedicated hardware.

Sampling bias: It is a systematic error due to a non-random sample of a population causing some members of the population to be less likely to be included than others resulting in a biased sample.
Time interval: A trial may be terminated early at an extreme value (often for ethical reasons), but the extreme value is likely to be reached by the variable with the largest variance, even if all variables have a similar mean.
Data: When specific subsets of data are chosen to support a conclusion or rejection of bad data on arbitrary grounds, instead of according to previously stated or generally agreed criteria.
Attrition: Attrition bias is a kind of selection bias caused by attrition (loss of participants) discounting trial subjects/tests that did not run to completion.

Univariate analyses are descriptive statistical analysis techniques which can be differentiated based on the number of variables involved at a given point of time. For example, the pie charts of sales based on territory involve only one variable and can the analysis can be referred to as univariate analysis.
Bivariate analysis attempts to understand the difference between two variables at a time as in a scatterplot. For example, analyzing the volume of sale and spending can be considered as an example of bivariate analysis.
Multivariate analysis deals with the study of more than two variables to understand the effect of variables on the responses.