Analyzing Big Data in Information Systems: Techniques & Challenges

This essay provides an overview of big data analysis within the context of information systems. It highlights the challenges associated with handling and interpreting large volumes of structured and unstructured data, emphasizing the scarcity of qualified business analytics professionals and the high costs involved in hiring them. The essay defines big data as a valuable resource for businesses, aiding in identifying opportunities, challenges, and effective solutions. It explores techniques such as statistics, A/B testing, and Natural Language Processing (NLP) used for analyzing big data. Furthermore, it discusses the characteristics of big data, including volume, velocity, and variety, and how these aspects contribute to understanding customer preferences, market competition, and overall business growth. The importance of big data technology in risk management, consumer behavior analysis, and targeted marketing campaigns is also emphasized, citing relevant research to support these points.

History on big Data
The big data is a massive information which is not easy to
handle. It helps the organisation to collect various large
organisations. The data is in the form of the unstructured
and structures data which assist in making various choice
for the benefit of the organisation. The challenges of these
are used to present the big technological organisations
which help in setting the momentum for storing the big
volume of data. It is very complicated but gives a deep
insight about the company and its performance.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
Big data is useful information about business which is spread in
different areas for different purposes which is collected, organized
and sorted at one place for preparing important conclusion. Big
data is important for finding what is important for business, what
are the challenges a business faces, how it can be overcome, what
are solutions and techniques which can be applied in business, it
also explains how spreader data is useful for covering untapped
areas and engaging customers for useful operations. It helps the
business to find support and a guidance which would help it in
increasing demand, retain customers and maximize customer
satisfaction. Big data is useful to understand growth related issues
in business, lagging behind in understanding massive and spreader
data, securing important data and information
Characteristics of Big data
Big data helps to collect useful information on the basis
of volume which describes data which is important and
which helps the business to have a proper guidance
which helps to know how a business shall be expanded.
Big data helps business to have an idea about customer
preferences, taste and demand and how they can
change the market competition.
Big data helps to obtain useful tests which can be
applied in the business according to demand in a
company which could be solved only with the help of
professional guidance.
Big data helps to understand sorting of data at one place
and learn machine learning as well which would be
helpful in calculation of spreaded data.The challenges of big data analytics
The main challenge that is faced by the analyst is of
sorting of the data. The information related to various
particulars which is obtained by the companies is very
large and it is not possible fir any intermediate person
who have less knowledge to interpret the data. The
troublesome situation is faced because there are very
less professionals who are qualified in the business
analytics. Also, it incurs very high costs for hiring these
professionals.
References
Özemre, M. and Kabadurmus, O., 2020. A big data
analytics based methodology for strategic decision
making. Journal of Enterprise Information
Management.
Wang, C., Zhang, Q. and Zhang, W., 2020. Corporate
social responsibility, green supply chain management
and firm performance: the moderating role of big-data
analytics capability. Research in Transportation
Business & Management, 37. p.100557.
Zhao, P. and Hu, H., 2019. Geographical patterns of
traffic congestion in growing megacities: Big data
analytics from Beijing. Cities, 92. pp.164-174.
How Big Data technology could
support business & Examples
This big data technology will help in the identification
of risk by analysing and evaluation the large data
evaluating the behaviour of consumers. It can be done
through observing the data by acquiring various
information by targeting the email campaigns. The
customer retention strategy is formulated by
forecasting the risks by managing. It indulges the risk
administration by lessening the adverse influence on
the company by lingering in the profitable zone.
Techniques that are currently available to
analysis big data
The techniques which are used by the company for performing the
evaluation is statistics which is used for gathering the large
information which is difficulty to organize and plan. This
information is used for experimenting and doing surveys. The
system of A/B testing is used for comparing the various type of
data and perform the test. The NLP is used for those data which
specifically requires the artificial intelligence for examining the
human language.