Information Systems & Big Data Analysis: Business Applications

This essay provides an overview of big data, defining it as a collection of organized or unorganized data that is large in volume and grows exponentially over time. It highlights the key characteristics of big data, including volume, variety, and velocity, which pose challenges for traditional data management tools. The essay also discusses the importance of big data for organizations in managing risks and improving decision-making performance, while addressing issues such as lack of understanding, data growth, and tool selection. Furthermore, it touches upon techniques for analyzing big data and how big data technology can support business by enabling better organizational decisions and enhancing understanding of consumers. The essay concludes with references to relevant research on big data analysis and perturbation using data mining algorithms. Desklib offers a range of resources for students, including solved assignments and study materials.

History on big Data
Big data may be defined as the collection of the data
which is very huge in numbers and yet growing day by
day exponentially with the increase in time. This data is
very large in size and very complex in nature that none of
the traditional data management tool can store or process
it in proper manner.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
The term big data may be referred to as those data which is
organized or unorganized and based on the valuable collection data.
The data can be collected from client, server or form the transaction
like sales, purchase, history of employee and many more.
Characteristics of Big data
There are different kinds of characteristic which is
associated with the big data form which some of them
discussed below
• Volume
• Variety
• Velocity
The challenges of big data
analytics
For the organization an important role is played by the bid
data which not only give assistance to them in managing
the risk but also assist them in improving their decision
making performance
Lack of proper understanding of big data
Data growth issues
Confusion while selecting the tool
References
Haoxiang, W. and Smys, S., 2021. Big Data Analysis
and Perturbation using Data Mining Algorithm. Journal
of Soft Computing Paradigm (JSCP), 3(01), pp.19-28.
How Big Data
technology could
support business &
Examples
Develop better organizational decision
Understanding the consumer
Techniques that are currently
available to analysis big data
• A/B test
• Data fusion and data integration