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

Big Data Analysis
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Contents
Introduction 3
What big data is and the characteristics of big data 3
The challenges of big data analytics 4
The techniques that are currently available to analyze big data
5
How Big Data technology could support business, an explanation
with examples 6
Poster 8
Conclusion 9
References 9
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Introduction
Data refers to the quantity, character or symbol that can be
transmitted in form of electrical signals for computer to perform operation.
Big data refers to the larger, complex sets of data from new sources. Data
which contains higher variety, huge in volume with more velocity. In this
report, explains the characteristics of big data and their challenges. It also
describes the techniques used for analogizing bid data and it also explain
the role of big data technology in support to business with relevant
example.
What big data is and the characteristics of big data
Big data contains data that is huge and yet growing with time. This
data is complex and are large in size, traditional method of data
management tools cannot process it efficiently and store it. Big data is
combination of different structured, unstructured and semi-structured
data collected by organizations that can help in machine learning,
projects and advance analytics application. Structured data can be
stored and processed in fix format. Unstructured data contains unknown
form of data has multiple challenges to process this data. Semi-
structured data includes both forms of data. Some of the characteristics
of big data are given
Volume – This refers to the size and amount of big data that
business has to manage and analyze. Data itself is related to the
extremely size and information gathered through different sources like
business processes, machines, social media platforms, networks and
human interactions. Big companies can handle the large amount of
data.
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