Big Data Analysis: Techniques, Applications, and Insights

This report provides a detailed analysis of big data, encompassing its characteristics, applications, and the challenges associated with it. It begins by defining big data and its core characteristics, including volume, variety, velocity, value, and veracity. The report then explores the practical applications of big data in various business contexts, such as reducing costs, increasing sales and revenue, and improving pricing decisions. Additionally, it highlights specific techniques like A/B testing, data fusion, and data integration. The report also touches on the importance of data mining, machine learning, and natural language processing (NLP). The report addresses the challenges of big data analytics, including the need for synchronization across diverse data sources and the shortage of professionals skilled in big data analysis. The conclusion summarizes the key takeaways and emphasizes the significance of big data in contemporary data science. The report is based on the provided references.

Introduction
Big data involves managing data which are the sets of large and
complex that traditional processing application which is inadequate to
capture, curate, manage and also to process the data with in a
reasonable amount of time . Big data can be used for predictive and
user behaviour analyst. This report comprise of what is big data, and
characteristics of big data.
Information Systems and Big Data Analysis
Name of the Student
Define big data and its
characteristics
Big data is a combination of structured, semi structure, and unstructured data
which is collected by organizations that can be minded for information that can
be used in machine learning projects predictive modelling and others and other
advance analytic application(Faccia,and et.al 2019).
information data sets.
Characteristics of Big data
•Volume
•Variety
•Velocity
•Value
•Veracity
The challenges of big data
analytics
• Need for synchronization across disparate data
sources
• Acute shortage of professionals who understand big
data analysis
• Getting meaningful insights through the use of big
data analysis
References
Guha, S. and Kumar, S., 2018. Emergence of big data research in operations management, information systems, and healthcare:
Past contributions and future roadmap. Production and Operations Management, 27(9), pp.1724-1735.
Faccia, Aand et.al 2019, August. Accounting information systems and ERP in the UAE: an assessment of the current and future
challenges to handle big data. In Proceedings of the 2019 3rd International Conference on Cloud and Big Data
Techniques that are currently
available to analysis big data
A/B testing :-
Data fusion and data integration
Data mining
Machine learning
Natural language processing (NLP) :-
Business Examples
• Reduce overall costs
• Increases sales and revenue
• Improving pricing decisions
• Provides a competitive advantage
• Increase efficiency in decision making
CONCLUSION
The above report include information about what is big
data and also what all are the characteristics of big data.