Page 123 - Contributed Paper Session (CPS) - Volume 6

CPS1847 Shariful I.
Big Data refers to collection of data sets so large and complex that it becomes
difficult to process using on-hand database management tools or traditional
data process applications. Big Data Analytics and Data process tiles a platform
to globalize the research by installing a dialogue between industries and
academic organizations and knowledge transfer from research to industry. Big
data can be characterized by 3vs: the extreme volume of data, the wide variety
of types of data and the velocity at which the data must be processed.
Although the big data doesn’t refer to any specific quantity, the term is often
used when speaking about petabytes and exabytes of data, much of which
cannot be integrated easily. Because big data takes too much time and costs
to money to load into a traditional relational database for analysis, new
approaches to storing and analyzing data have e emerged that rely less on
data schema and data quality. Although the demand for big data analytics is
high, there is currently a shortage of data scientists and other analysis who
have experience working with big data in a distributed, open source
environment. In the enterprise, vendors have responded to this shortage by
creating Hadoop appliances to help companies take advantages of the semi-
structured and unstructured data they own. Big data can be contrasted with
small data, another evolving term that’s often used to describe data whose
volume and format can be easily used for self-service analytics. A country
quoted axiom is that “big data is for machines; small data is for people”.

2. Methodology
Industry press is enamoured by the 4 V’s of Big Data. These are Volume,
Velocity, Variety and Veracity. Volume is referring to the size of the data.
Velocity is referring to the speed of how data is collected and consumed.
Variety referring to the different kinds of data consumed, from structured data,
unstructured data and sensor data. Veracity is referring to the trustworthiness
of the data.
The Methods of big Data can be described by the following characteristics:
1. Volume-The quantity of data that is generated is very important in this
context. It is the size of the data which determines the value and
potential of the data under consideration.
2. Variety- The next aspect of Big Data is its variety. This means that the
category to which Big Data belongs to is also a very essential fact that
needs to be known by the data analysis.
3. Velocity-The term ‘velocity’ in the context refers to the speed of
generation of data or how fast the data is generated and processed to
meet the demands and the challenges which lie ahead in the path of
growth and development.
4. Variability- This is a factor which can be a problem for those who
analyse the data. This refers to the inconsistency which can be shown

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