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

This presentation provides an overview of big data analysis, including its history, challenges, techniques, characteristics, and how it supports businesses. It also includes examples and references. The presentation is relevant to the Information Systems and Big Data Analysis course (ISBDA).

History on big Data
Around 300 BC, Ancient Egyptian
use techniques to capture the large
volume of data in the Alexandria
library. It was also used by the
roman empires in determination of
its armies.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
Big data is defined as the data which is considered large in
volume. In other words, it refers to the structured and
unstructured data which is huge and is hard to manage is
known as Big data
Characteristics of Big data
The characteristics of big data comprise of
the five V's which are described as follows:
• VELOCITY
• VERACITY
• VOLUME
• VARIETY
• VALUE
The challenges of big data
analytics
1. Visual representation of big data
2. Data inaccuracy
3. Collection of the amount of data
4. Collection of data from multiple sources
5. Collecting meaningful and real time data REFERENCES
• Khalid, Z. M. and Zebaree, S. R., 2021. Big data analysis
for data visualization: A review. International Journal of
Science and Business, 5(2). pp.64-75.
• Silva, B.N., Diyan, M. and Han, K., 2019. Big data
analytics. In Deep Learning: Convergence to Big Data
Analytics (pp. 13-30). Springer, Singapore.
How Big Data technology could support business &
Examples
Big data technology helps a lot in running and promoting
business operation as they help in effectively keeping and
analyzing data related to customers wants and requirement.
In another words, through the technology companies are able
to easily understand about the trend, taste and preference of
customers and the manner in which they can be satisfied in
best possible way. For example: Tesco has make use of big
data technology to accumulate information related to what is
actually happening in external environment to find
alternative method that could be used to meet customers
expectancy.
Techniques that are currently available to analysis big data
A/ B testing: It is one of the data analysis techniques that involves
comparison of control group with varieties of test group in order to
derive what changes or method that could be used to achieve the set
objectives.
Machine language: It is another method that are used by
companies for big data analysis that is well known in artificial
intelligence.
Data mining: Moreover, the data analysis technique that has been
used by company is data mining in which it extracts a pattern from
large set of data through making use of both machine and statistics
method.
Data fusion and data integration: It is data analytical method in
which combination of set of technique that are used to analysis and
integrate data from different sources in order to find a particular
solution.
It is a type of data
that help the day to
day operation of the
business to
inundate. It is not
only the data that is
important to
business.