Information Systems and Big Data Analysis

This report explains the characteristics of big data, challenges faced in big data analytics, and techniques to analyze big data. It also discusses how big data technologies assist businesses in making better decisions and improving customer retention services.

Information Systems
and Analysis of Big
Data

Table of Contents
INTRODUCTION...........................................................................................................................3
MAIN BODY...................................................................................................................................3
1.Define big data and also explain the features of big data?.......................................................3
2.What are the challenges faced in big data analytics and the techniques which are currently
accessible to analyse big data......................................................................................................3
3. In what ways Big Data technologies can prove to be an assistance for businesses, provide
usage of examples where necessary............................................................................................3
CONCLUSION................................................................................................................................4
REFERENCES................................................................................................................................5

INTRODUCTION
An information system is a type of formal, sociotechnical and organizational system which
is made to collect, process, store and allocate the information. Big data refers to the large variety
of data which arrives in the business organisations in huge quantities (Deckro and et.al., 2021).
The report presented below involves three different parts: the first part of the report involves a
brief explanation of big data and the characteristics of the big data. The second part of the report
comprises of the challenges faced in big data and the various techniques that are available for
dealing with big data. The last part of the report involves the description of the different ways in
which big data assists the businesses to deal with the information constituted in it.
MAIN BODY
1.Define big data and also explain the features of big data?
Big data refers to the type of data which is in huge variety and great quantity that is way
complex to handle or dealt in the conventional manner of using the old traditional data
processing software’s. It contains the data from many fields and the variety of statistical higher
complexity data from new data sources. The volume of data is so large and massive that any
individual conventional software cannot handle it on their own. But these big data sets are
massively helpful in assisting the business with the solution of various problems that would be
impossible to tackle otherwise (Green and et.al., 2018). The characteristics of big data are as
follows: Volume: It refers to the size and the amount of the big data which is received and attained by the
companies to deal with, manage and evaluate for reaching conclusions.
 Variety: This refers to the diversity and the different types of data that is dealt by the business. It
involves all the various forms of data sets: unstructured data, structured data and even the raw
data.

 Velocity: The velocity refers to the rapidity at which the companies receive the data sets, the pace
at which they manage, analyse and derive conclusion from the data sets. This speed determines
the time required for realising the final results from the data set available. Veracity: This determines the accuracy and correctness of the big data and information sets which
help in determining the confidence of the management in the final conclusions which will be
derived from the data set available.
 Value: It is the most essential characteristic of big data from the business objective. This
determines the insights and analysis which the business will attain from evaluating the big data
which will be then helpful in effective operations, strong customer relations and efficient
quantitative business advantages (Gupta, Kar, Baabdullah and Al-Khowaiter, 2018).
2.What are the challenges faced in big data analytics and the techniques which are currently
accessible to analyse big data.
There are numerous challenges that the businesses face in dealing with the big data sets as
the actual implementation of the data sets involves various hurdles that are faced by the
companies. These challenges need immediate action as failure in assisting the data properly may
lead to unwanted results that may prove not good for the company. The challenges involved are:
1) Privacy and security of data: Many business organisations fail miserably in maintaining
frequent checks on the big data of their businesses due to the large quantity of data which
is generated. It becomes a necessity to keep regular security checks and keep the data
under privacy observation to avoid any unwanted security fails with the company’s data.
This challenge holds importance in various areas such as legal, conceptual, sensitive as
well as technical.
2) Confusion with selection of data tools: the selection of the significant data tool
depending upon the variety and volume of data is one of the biggest challenge face by
companies handling big data. The businesses are sometimes not able to assess the
characteristics of the data and hence fail to apply the right technology in analysing the big
data (Javaid and et.al., 2021). This sometimes results in wastage of money, efforts and
even the business technology.
3) Data integration: The data in a corporate business environment comes from a various
number of sources which are different from one other. The task lies in combining this big

data from all these different sources in the form of an organised report. Integration of data
is an essential part for reporting analysing and providing business intelligence to the
company.
Big data techniques refer to the various specialised processes and techniques that assist to
deal with the large data sets (Kushwaha, Kumar and Kar, 2021). The techniques utilised for
analysing and treating the big data sets are mentioned below:
1) Data mining: It is a common tool utilised by various business organisations for the
purpose of analysis of the big data sets by using a combination of the methods from
machine learning and statistics within the database management.
2) A/B Testing: this technique of data analysis comprises of a control group which contains
various different test groups, for the purpose of determining what changes will develop
the data sets and its variables.
3) Data Fusion and data integration: By integrating and combining various data
techniques containing data from various different sources, the insights then received are
much more effective and potentially accurate in comparison with those results which are
achieved through a single data source (Wang and Wang, 2020).
4) Natural language processing: It is also termed as subspecialty of the subject of computer
science, artificial intelligence and the linguistics as a subject area. This technique of data
analysis is utilised for analysing and evaluating the human language of big data by using
various algorithms.
3. In what ways Big Data technologies prove to be an assistance for businesses, provide usage of
examples where necessary.
Each and every business organisation, irrespective of its size and capacity requires big data and
the insights of the big data. The reason behind is the high value of importance that the companies
receive due to the insights from these data sets (Mazanec, 2020). It assists businesses in
understanding the customers profile of the business, the target business audience and the success
of the company’s products or services in the market and much more. Few of the ways in which
big data is helpful to the business organisations is as follows:
1) Improving insights of customers: The big data involves data combined from various
different sources and hence provides the business with a variety of data to extract useful
business information from. These includes traditional customer data sources like support

calls, credit reports, social media activities and many ore. These sources together provide
the business with some essential results which help business to improve the customer
insights (Poltavtseva and Kalinin, 2019).
2) Make better business decisions: Big data provides businesses with the essential tools
necessary for making better decisions ion the basis of the data sets available. The mass
availability of the data assists the businesses in making better decisions for the company
as it has access to large data variety along with various useful insights.
3) Improve customer retention service: The big data in a business organisation provides it
with useful business insights and analysis that help the business in improving its overall
services. It acts as a guide to help the business organisations top generate a better
responsive customer services and better the business products along with the services
being provided.

CONCLUSION
From the above report, it can be concluded that big data is an essential part and a
developing issue in today’s times and is growing at a rapid pace. The characteristics, usage and
importance of big data and its techniques for the present business scenario is the major point
concluded in the report above. The various ways in which the data sets help the businesses
involve improvement of customer retention services, making better decisions as concluded from
the report. The final conclusion made was that the availability of big data is very beneficial to
business organisations and a proper handling and analysis of the same could prove to be greatly
advantageous to the business organisations.

REFERENCES
Books and Journals
Deckro, J., and et.al., 2021. Big data in the veterans health administration: a nursing informatics
perspective. Journal of Nursing Scholarship, 53(3), pp.288-295.
Green, S., and et.al., 2018. Big data, digital demand and decision-making. International Journal
of Accounting & Information Management.
Gupta, S., Kar, A.K., Baabdullah, A. and Al-Khowaiter, W.A., 2018. Big data with cognitive
computing: A review for the future. International Journal of Information
Management, 42, pp.78-89.
Javaid, M., and et.al., 2021. Significant applications of big data in Industry 4.0. Journal of
Industrial Integration and Management, 6(04), pp.429-447.
Kushwaha, A.K., Kumar, P. and Kar, A.K., 2021. What impacts customer experience for B2B
enterprises on using AI-enabled chatbots? Insights from Big data analytics. Industrial
Marketing Management, 98, pp.207-221.
Mazanec, J.A., 2020. Hidden theorizing in big data analytics: With a reference to tourism design
research. Annals of Tourism Research, 83, p.102931.
Poltavtseva, M.A. and Kalinin, M.O., 2019. Modeling big data management systems in
information security. Automatic Control and Computer Sciences, 53(8), pp.895-902.
Wang, S. and Wang, H., 2020. Big data for small and medium-sized enterprises (SME): A
knowledge management model. Journal of Knowledge Management, 24(4), pp.881-897.