Big Data Analysis & Information Systems: Trends, Challenges & Examples

This report provides an overview of big data and its relationship with information systems. It defines big data, outlines its characteristics (volume, velocity, variety, veracity, and value), and discusses various techniques used for analyzing big data, including A/B testing, machine learning, and data mining. The report also addresses the challenges associated with big data analytics, such as a lack of understanding, data growth issues, and a shortage of data professionals. Furthermore, it explores how big data technology supports businesses by enabling better decision-making, boosting customer acquisition and retention, and solving advertising problems. The report concludes that big data and information systems are crucial for business organizations, enabling them to evaluate data insights with accuracy and validity.

History on big Data
The information system is study of academic systems in
reference to information and networks of hardware and
software which is used by organization for collecting,
processing, storing data. The big data is concept of
managing large and complex data sets that traditional
processing application software were inadequate to
capture, manage and process data within a reasonable
amount of time.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
The big data can be used for predictive and user analytic behavior.
It is a field of analysis and extracting information or dealing with
data sets which are too large or complex that can be deal by
traditional data processing information. Its is usage of advance
analytic techniques which involves structured, semi-structured and
unstructured data form different sources in diverse sizes from
terabytes to zettabytes against large data sets.
Characteristics of Big data
• Volume
• Velocity
• Variety
• Veracity
• Value
The challenges of big data
analytics
• Lack of proper understanding of big data
• Data growth issues
• Lack of data professionals
References
• Al_Janabi, end et.al., 2018, November. Multi-level
network construction based on intelligent big data
analysis. In International Conference on Big Data and
Smart Digital Environment (pp. 102-118). Springer,
Cham.
How Big Data technology could
support business & Examples
In business organization understanding target audience
and customer preferences the big data plays an significant
role by providing needed valuable data and insights.
• Better decision making
• Boosting customer acquisition and retention
• Solves advertising problems and offers marketing
insights
Techniques that are currently
available to analysis big data
• A/B testing
• Machine learning
• Data mining
Conclusion
It is being concluded that big data and information system is an
crucial concept for the business organization which helps in
validating information. The companies are now able to evaluate
data insights with accuracy and validity of data.