Information Systems and Big Data Analysis: Techniques and Examples

This report provides an overview of big data analysis, defining it as a complex process involving the systematic examination of large datasets to identify hidden patterns, market trends, and customer preferences. It highlights the main characteristics of big data, including volume, and discusses the challenges associated with its analysis, particularly the lack of skilled professionals. The report also covers various techniques used in big data analysis, such as data fusion and data integration, explaining how these methods support businesses in drawing critical evaluations from diverse data sources like social media and market trends. Furthermore, it emphasizes how big data technology can support business operations by turning data into a valuable asset, improving management activities through insights gathered from customer desires and online platforms, referencing examples from e-business entrepreneurship and intelligent information systems.

History on big Data
Big data analysis is termed as the complex process which
involves systematic examination of big data in order to
identify vital information's related to hidden patterns,
current market trends as well as supports the company in
timely ascertaining customer wants and desires. The main
aim of big data analytics is to foster data driven business
decisions in order to enhance the chances of success. The
report will cover explanation of big data and the main
characteristics of big data. In relation to this, the report
will highlight challenges while doing big data analysis and
will also cover techniques of doing big data analysis.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
Big data is basically considered as data which is too large and
complex in a way that is impossible to process while using
traditional methods of storing data. This supports the organisations
to process large information in the cost effective manner as well as
also provides with innovative methods of information processing
that assist the companies to improve insight about business
operations.
Characteristics of Big data
Volume:
The big data is the collection of varied forms of
data consisting of enormous size. The volume of big
data is generally consist of vast data generated from
different areas and sources of external as well as internal
environment of business. The big data includes huge
volume of varied form of information's such as
processes of business, customer preferences, market
demands and many more.
The challenges of big data analytics
Lack of skilled professionals:
In order to run modern data analytics tools and
systems the skilled data science professionals are
required by many big organisations. One of the
biggest challenges that the company faces is lack of
data engineers in the market. This challenge force the
company to use invest extra money training and
recruitment process(Song, Xu and Dolma, 2019).
References
Ye, Z., Zheng, J. and Tu, R., 2020. Network
evolution analysis of e-business entrepreneurship:
big data analysis based on taobao intelligent
information system. Information Systems and e-
Business Management, 18(4), pp.665-679.
How Big Data technology could support business
& Examples
Data will become an asset:
The data is used by almost every business
companies in order to improve its operation and
management activities. The data can be collected
from the customer desires, website and social media
platforms.
Techniques that are currently available to analysis big data
Data fusion and data integration:
This set of technique supports business organisation to analyse
big data and draws critical evaluation by integrating data from different
sources such as social media platforms or from market trends. In
relation to this, this tool works more accurate and efficient when the
information is analyse from the single source.