Big Data Analytics: Characteristics, Challenges, Techniques and Business Support

Business Management
BMP4005
Information Systems and Big Data
Analysis
Poster and Accompanying Paper
Submitted by:
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Contents
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Introduction p
What big data is and the characteristics of big data p
The challenges of big data analytics p
The techniques that are currently available to analyse big data
p
How Big Data technology could support business, an explanation
with examples p
Poster p
References p
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Introduction
Big Data is the field that analyses and extracts the information which helps in
dealing with the data at large scale (Favaretto and et.al., 2020).
The report will analyze characteristics of big data and what it signifies. Challenges
of big data analytics will also be identified and described appropriately. Along with this,
techniques available to analyze big data will also be known and explained at large scale.
And how big data supports business with explanation of examples will be provided. This
will help in evaluating all essential information which will be identified and then will lay
importance to big data and its analytics.
What big data is and the characteristics of big data
Big data is the field that idealizes the ways to systematically evaluate and extract
information and dealing with sets of data which are too large or complex in dealing with
data processing software traditional in nature. Big data helps in analyzing and evaluating
the information at large scale. Big data is the data which is of huge size.
Characteristics of big data defined are –
Volume – Size of the data plays very important role and big data is itself very big in size.
Volume of big data helps in determining the value out of data. Volume is the main
characteristic which help in dealing with the data while having solutions at large scale
and this helps in knowing major scale and basis through which the big data can be
analyzed effectively and significantly (Sun and et.al., 2018).
Variety – Variety refers to sources which are heterogeneous in nature along with the
nature of data defined as unstructured and structured. Data nowadays is send through
emails, PDF’s, monitoring devices, videos, audio etc. The unstructured data incurs some
certain issues for mining, analyzing data and storage which is being evaluated at large
scale and this helps in knowing variety through which type of data is being analyzed.
Unstructured data possess issues which are known effectively.
Velocity – Velocity refers to generation of data through speed. It means that data is runs
fast and is being generated by fulfills demands, determines potential of data for its
evaluation. Velocity deals with data flows from sources like social media sites, mobile
devices, application logs, etc (Ghasemaghaei, 2019). The flow of data is continuous and
massive and is evaluated at large scale. This helps in analyzing basis of data through
which all aspects are being considered.
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