Information Systems and Big Data Analysis: A Comprehensive Overview

This report provides an overview of big data analysis and its integration with information systems. It covers the challenges associated with big data, such as data security, fake data, and non-compliance with privacy laws, and explores the advantages like improved decision-making, cost reduction, and operational efficiency. The report details various big data techniques, including A/B testing, data mining, and machine learning, and highlights the characteristics of big data: volume, velocity, and variety. Furthermore, it provides examples of big data applications in business, such as Walmart's use of big data to personalize products. The report also references relevant sources for further reading on the topic.

INTRODUCTION
Data analysis is a procedure to examine sets of data to identify the
trends and to draw a conclusions regarding the information it may
contain. Information system is an set of elements that collects, stores
and process the data in order to provide knowledge, information and
digital products.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
Big data analysis is an components of several information in huge quantity which
cannot be stored, processed or being analysed with traditional methods. Big data
refers to a collection of huge sets of data with these are several framework,
techniques and tools involved. There are various benefits of using big data
analytical such as.
• It helps in making quick and better decisions
• Cost reduction and operational efficiency
• Provides an improved data-driven got to market
Characteristics of Big data
There are various benefits of using big data analytical such as.
Variety-
Velocity-
Volume-
The challenges of big data
analytics
There are various benefits of using big data analytical such as.
• Exponential growth
• Big data tools
• Securing
• Data security and protection
• Fake data generation
• Unsecured data sources
• Non-compliance to privacy laws
References
Choi, D. and et. al., 2021. Design and implementation of an academic expert system through big data analysis. The Journal of Supercomputing, 77(7),
pp.7854-7878.
Fedin, F.O. and et. al., 2019, September. Assessment of intelligent decision support systems effectiveness in technological processes of big data processing.
In 2019 International Russian Automation Conference (RusAutoCon) (pp. 1-6). IEEE.
Techniques that are currently
available to analysis big data
• A/B testing
• Data mining
• Machine learning
• Data fusion and data integration
Big data advantages
• The big data analytical tool helps in predicting the outcomes
accurately
• Big data analytical help enterprise to generate more sales leads
that will boost the revenue.
• It provides a insight that helps in keeping the business a step
ahead from their competitors.
Examples of usage of big data in business are mentioned below.
Walmart
It leverages big data and data mining to make personalised
products for their customers. Walmart is using NoSQL and
Hadoop technology which allows customers to access in real time
data in order to collect from different sources.