Information Systems and Big Data Analysis: Key Concepts Review

This essay provides an overview of big data, tracing its history back to 1663 and highlighting the challenges associated with its analysis, such as data scarcity and long response times. It defines big data as a vast amount of information that surpasses the processing capabilities of traditional data management software. The essay discusses techniques like A/B testing and data fusion for analyzing big data, along with the five V's (Volume, Value) characterizing it. Furthermore, it emphasizes how big data technology supports businesses by providing better consumer insights through various sources, including conventional customer information, external sources like monetary transactions, and social media activity. The document is contributed by a student and available on Desklib, a platform offering AI-based study tools and a repository of academic resources.

History on big Data
Big Data is considered as a tool or software
which is used in collecting, analysing, and
managing the large number of complex data.
The very first trace of the big data was found in
the year 1663.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
Big Data provide the huge amount of
information that improves the exponential rate.
It is so large that none of the old data
management software cannot be able to process
the effectively.
Characteristics of Big data
The characteristics of Big data can be describe by the
five v's which are as follows-
Volume- It refers to the size and
amounts of big data which the organisation manage
or examine.
Value- The next and very important
“V” is value. It means the value of big data for the
business organisation. It is very important because
big data provide the insight information of the
business which help in business decision as result the
business organisations are able to earn huge amount
of profit
The challenges of big data analytics
Lack of data- The very first challenge of the big data
analytics is the lack of data due to which the analytics
does not able to generate the new insight on the right
time. This thing also leads to raise the problem for the
business organisation also it is because they are not able
to take the right decision so that they can expand their
business operations.
Long Dara response- It is already
discussed above that big data contain a large amount of
information which take a enough time to process.
Sometime the companies require the data very quickly but
due to the very long procedure they are not able to
arrange the information when it required. So this is also a
challenge which is faced by the big data analytics.
How Big Data technology could support business &
Examples
Better Consumer Insight- The very first benefit of big
data technology is that it provide the consumers insight.
Due to this the business are able to find out their targets
which they have to achieve in the future. Various
sources of big data through which the business get the
consumer insights are as follows-
Conventional sources of customer information, like
purchases and calls support.
Outside sources like monetary transactions and credit
reports.
Social media activity and many more .
Techniques that are currently available to analysis
big data
A/B testing- This techniques helps the business in
comparing the two set of groups. Through this they
are able to find out the areas which have to be
improve so that the reliability of data can be
maintained properly. This technique is very useful
because it almost find out all the errors which
includes in the big data.
Data fusion and data integration- In
this technique the set of different techniques are
combined through which the data can be analyse and
integrated from the various sources and solutions. It
has to be done because the data collection from one
source is considered more reliable and accurate then