Big Data Analytics in Business

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Big data refers to a field which provide systematic
extraction of information from a number of data sets
that are too large and complex to be dealt with
traditional ways of data processing. It is often seen that
the data that have a number of cases a rose with great
statistical power and high complexity a leading towards
false discovery rate. Big data helps in including the
challenge of capturing data, storing data, analysing data,
sharing data, transferring data, updating data,
visualizing data and soon.
These are all the sources which produce different data which are to be
collected, stored as well as analyse successfully. Along with this the
data scientist as well as analyst or not only limiting their job to
collecting data from one source but there are a number of different
sources which are providing data.
Velocity: When considering the amount of data its volume and
the variety there is consistent flow of data. This gives the birth to 3rd
characteristic that is velocity . Velocity of data means that more data is
available on certain days and due to this the velocity of data analysis is
also required to be high. There are data professionals who gather data
over time and the date at the end of week or a month or quarter or rather
hide and that at other time of days. Due to this velocity is a major
characteristic of big data which is to be analyse successfully.
Veracity: Voracity refers to the accuracy, quality as well as
trustworthiness of the data that is collected. The reliability of data needs
to be distinctive in order to make sure that the data which is collected is
accurate and conclusions can be drawn from it. It is often required to
understand the valuable sources of information from which the big data
can be analysed successfully. When the veracity of data is low it is often
estimated that bad decisions can be evaluated and drawn due to the data.
Information Systems and Big
INTRODUCTION Marketing and Finance Department
The characteristics of big data can be characterized into
four components as mentioned below:
Volume: Volume is the first and major
characteristic of big data which makes the dataset big in
its size which is to be evaluated. The date upsets are
usually stretch to petabytes and exabytes. There are
huge volumes of powerful data present and powerful
processing techniques are required in order to assess this
data.
Variety: The variety which is present in big data is very
high. Examples can be taken of different email, CRM
system, mobile data as well as Google advertisements
that are included in different data sets.