Information Systems and Big Data Analysis - History, Techniques, Challenges, and Business Examples

This presentation provides an overview of Information Systems and Big Data Analysis, including its history, techniques, challenges, and business examples. It explains how big data analytics helps businesses and organizations make better decisions by revealing hidden information. The presentation also covers the characteristics of big data and the techniques currently available for analyzing it.

History on big Data
Big data analytics helps businesses and organisations
make better decisions by revealing information that would
have otherwise been hidden. There are lots of techniques
and tools available for analysis . The process includes data
analysis, cleansing, mining, visualization, integration and
management. The main aspect of big data is to help in
evaluation of business on the basis of current situation.
Information Systems and Big Data Analysis
What is big Data
It is the process which is generally used test various and massive
amount of data sets to uncover market trends and more. It helps a
business to come up with effective decisions . Big data refers to the
big complicated structured and unstructured groups of data which
are getting generated quickly and transferred from the vast sources
variety. (Lin, H.Y. and Yang, 2019)This process includes data
analysis, cleansing, mining, visualization, integration and
management
Characteristics of Big
data
• Volume
• Variety
• Velocity
• Veracity
• Variability
The challenges of big data
analytics
• Lack of coordination
• Solving the wrong problem
• Dated Data
• Dated Data
• Non optimal infrastructure
References
Li, and et, al., 2020, April. Security Management System Construction of Information System Based on Big Data Analysis.
In 2020 International Conference on Urban Engineering and Management Science (ICUEMS) (pp. 546-549). IEEE.
Lin, H.Y. and Yang, S.Y., 2019. A cloud-based energy data mining information agent system based on big data analysis
technology. Microelectronics Reliability, 97, pp.66-78.
Tao, and et, al., 2020. Utilization of text mining as a big data analysis tool for food science and nutrition. Comprehensive reviews
in food science and food safety, 19(2), pp.875-894.
Techniques that are currently
available to analysis big data
• A/B testing
• Data fusion and data integration
• Machine learning
• Statistics -
Business Examples
• Communication with Consumers
• Re-Develop Products
• Risk Analysis
• Data Security
• New Revenue System