Information Systems & Big Data Analysis: Business Support & Examples

This essay provides an overview of big data, defining it as a collection of organized and unorganized information gathered from various sources, including market studies, user feedback, and industry data. It highlights the challenges associated with big data analytics, such as data growth, tool selection, and a lack of understanding. The essay also explores techniques used for big data analysis, including principal component analysis and linear discriminant analysis, along with the characteristics of big data, such as volume, variety, velocity, and variability. Furthermore, it discusses how big data technology can support businesses by improving product quality, enhancing decision-making, reaching capable users, and generating income. Examples and references are provided to support the discussion. Desklib offers a range of study tools and resources for students seeking further assistance with similar topics.

History on big Data
Big data is a collection of the organized and unorganized
data it is gather on the basis of the information that is
generated by the market study and feedback and
responses of the users and individuals (Lin and
Yang,2019.). It consist some techniques and other tools to
integrate the details and other information that are
beneficial for the company and industry.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
In this current era, technologies development and creativity are
consider in massive details during managing these tools utilized
by different industry to give growth for their company (Jiang and
et., al., 2019). These technologies leads to gain in gathering data
to grow different sources like merchandising governing bodies
and many more.
Characteristics of Big data
• Volume
• Variety
• Velocity
• Variability
The challenges of big data
analytics
• Issues of data growth
• Confusion in tool choice
• Lack of understanding
References
Carra, G., and et., al., 2020. Data-driven ICU
management: using Big Data and algorithms to improve
outcomes. Journal of Critical Care, 60, pp.300-304.
Feng, P., 2019, January. Big data analysis of e-commerce
based on the internet of things. In 2019 International
Conference on Intelligent Transportation, Big Data &
Smart City (ICITBS) (pp. 345-347). IEEE
How Big Data technology
could support business &
Examples
• grows the goods quality
• Better decision making
• Reaching capable users
• Using the sources to make income
Techniques that are currently
available to analysis big data
• Principle component analysis
• Linear discriminant analysis