Exploring Information Systems and Big Data Analysis Trends

This essay provides an overview of big data and its analysis within the context of information systems. It defines big data, highlighting its characteristics such as volume, variety, velocity, value, veracity, and visualization. The essay discusses the challenges associated with big data, including lack of understanding and improper integration, and explores techniques currently available for analysis, such as predictive analytics, machine learning, data mining, data virtualization, and data quality. It further explains how big data technology supports businesses by extracting data and information from large and complex structures and databases. The essay concludes by referencing a study on big data quality, emphasizing the importance of understanding and managing big data effectively.

History on big Data
Big data refers to complex data which is large in number and
hard to deal. It is majorly used for management of data in
different organizational structures. These are those data which
cannot be analyzed or assessed by traditional methods, so to
analyze these huge and complex data big data analytics is
used. This model helps in transforming complex data into
understandable format. This analysis model also helps
different companies to inspect and scan distinct trends and
patterns.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
Big data analysis helps different businesses to understand large data
resources with hi- tech techniques. These data includes structured,
unstructured and semi-structured data within the organization. This data
provide different decision tools to the businesses which help the
enterprises to take smart business decisions which also enhances
organizational efficiency .
Characteristics of Big data
There are several characteristics that are associated with Big
data. There are six key characteristics of Big data named as
Volume, Variety, Velocity, Value, Veracity and Visualization.
The challenges of big data
analytics
Big data are usually huge, complex and extensive. As these
data are growing rapidly with time, there are several massive
challenges that are associated with these data. Some of these
challenges has been discussed below-
• Lack of Understanding
• Improper Integration References
Taleb, I., Serhani, M.A. and Dssouli, R., 2018, July. Big data
quality: A survey. In 2018 IEEE International Congress on Big
Data (BigData Congress) (pp. 166-173). IEEE.
How Big Data
technology could
support business &
Examples
Big data technologies is designed to extract data and
information from large and complex structures and
databases.
Techniques that are currently
available to analysis big data
Big data consists of huge and complex process and technology plays
a huge role in this analysis. In order to collect these data several
differentiated technologies has been used. Some of these
techniques are Predictive Analytics, Machine learning, Data mining,
Data Virtualization, Data Quality etc.