Big Data in Business Management Information Analysis Systems Report

This report provides an overview of big data methods and their characteristics, highlighting the importance of big data technology for organizations. It discusses the challenges of big data analytics, including data security and complexity, and explores techniques such as machine learning, data mining, and statistics used to analyze big data. The report emphasizes how big data technology can support business innovation, flexible supply chains, and data privacy, providing examples of companies like Marks and Spencer that utilize big data to secure consumer data. The document concludes with a discussion of data-driven innovation and the importance of real-time data analysis for maintaining a global supply chain.

Business Management
Information Systems and Big Data
Analysis
Poster and Accompanying Paper
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Contents
Introduction p
What big data is and the characteristics of big data p
The challenges of big data analytics p
The techniques that are currently available to analyses big data
p
How Big Data technology could support business, an explanation
with examples p
Poster p
References p
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Introduction
Big data methods refer to the wider data that links to the various consumers in the
marketplace. As it is very essential and important segment for the organization to maintain
there technology of big data in terms of it’s structure. Various businesses or organizations
should utilise this technology in order to safe and successful growth of the business. The
following report is based on the big data techniques and their principle or features, various
kinds of the challenges or issues, methods that are currently there too examine the big data.
Moreover it will include the way in which the technology of the big data can help the
organization to get long term profitability and success (Grover, and Kar, 2017).
What big data is and the characteristics of big data
Data is gained from numerous of sources numbers, forms text, video, audio, photos.
When a person opens up an application Like Google Maps and casually travel from one
place to another with electronic device like mobile then it can lead to generation of data
consistently. Large quantity of helpful data that an organization and business can store,
manage, visualize and evaluate because current data tools are not that reliable to manage
this sort of complexity and volume. In other word, big data technology referred to as a
larger term of the storage of data that link to the variety of consumers in the management.
It is one of the vital and essential section for the management in order to manage their big
large data in case of evolution of orientation of it (Martin, and Schuurman, 2020). The
business of the organization has to make an effective and efficient operational software for
keeping the operations and functions that are linked with techniques of big data.
Moreover, every connection with the technology gains new data that can be utilised to
describe. In order to cater to the target consumers of the organization, management can
utilise these research to aim of boosting, making efforts and company strategies. The need
of the big data and its usage has been known for a very long time, technology has only
made it possible to evaluate worst quantity of the data consistently and quickly with
efficiency. Data is both unstructured and structured when which will be combined and
evaluated in the few years in accordance to know the deep inside and likely assist to
predict the future. As collection of data and interpretation of it has become more
convenient and accessible, wake data will assist small businesses two large organizations
(Ismail, Shehab, and El-Henawy, 2019).
Characteristics of big data :
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Features of big data is a combination of criterion that shows various approaches to analysis of
big data and characteristics of big data are described below :
There are four V’s of big data that are value , variety, volume and velocity (Ghasemaghaei,
2020).
It refers to the big size of data that is generated consistently from the various sources like
networks, machines, social media platforms, Internet, human interaction, and various others.
The four the four V’s and its characteristics are mentioned below:
In the similar manner that the total variety and volume of data companies maintain and collect
has now evolved, so this has the speed at which it is generated and maintained. It is one of the
biggest myths in respect of big data that velocity is one of the most crucial elements of big
data.
It consist of variety of kinds involving unstructured, structured and semi structured data
combined from a multiple of source. Earlier, data had to be gained from different
spreadsheets and databases. However, Velocity of big data refers to the authenticity, quality
and amount of errors of the data gathered..
The challenges of big data analytics
Big data evaluation that links effective and efficient way of the divisions in the
organization. Nowadays almost every business our organization are utilising this technique of
big data effectively and efficiently . The organization requires two focuses on big data
methods in order to capture and maintain the customer satisfaction in order to sustain the long
term growth and success of the business. As it is a basic necessity of big data analysis in
accordance to keep the customer ‘s personal information in an efficient and effective way
(Patel, Shah, and Shah, 2020).
The various basic challenges or issues of the big data technique are described below briefly:
 Security of data – It is very much crucial in maintaining and controlling the large
data of their consumers from any type of virus or hacker at the broader and specific
term of the division. One of the most modified set of data from various sort of the
section can get present the orientation of leader or manager in giving security to the
data of the customer which can help in getting the trust of the consumer and
maintaining their loyalty for the future growth. Various terms of the international
methods that functions several operations like spyware, malware etc. It can have the
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direct effect on the wider source of data with high effective security of the data
(Ashabi, Sahibuddin, and Haghighi, 2020)
 Complexity of data - This term relates to the complexity in the managing and
storage of the big data methods, as it is very crucial for the professional to overcome
the challenges and issues in an effective way. The source of data must be examined
and analyzed in a secure manner in order to prevent the viruses or any kind of issue to
harm the data or information. Experts in the organization develop several records in
order to keep the data into it for a longer period of time that can be utilized anytime by
the firm.
 Quality data - By maintaining the quality of the collection of the data then it can
be tough for the firm to store and save it away from the viruses or any other problems,
which can harm the information. As it will get helped by managing and clearing out
the false data also error in the area of the business that stores the data. Moreover, it
will be very beneficial for the firm to manage all the issues in order to save the source
of the data
The techniques that are currently available to analyse big data
 Machine learning - It refers to evaluating its various ways of sector that keeps a
message at it will affect the robotics learning, artificial intelligence which can directly
related with the method and framework of the computer science with appropriate
schedule of the management.
 Data mining - It refers to the efficient method that is gained by the
organization in order to maintain their dealings with large data analysis. Data
mining can affect the divisions which deal with the suitable and possible terms
that include machine and figures (Sheeran, and Steele, 2017).
 Statistics - It refers to the big data technology that includes various methods of
process to keep the files in the way of source of the data that are usually dependable
on the scalable and diverse area of the division. It also supports in keeping an effective
data that should be there in the business of any industry which produced goods or
services for market share with effectiveness.
How Big Data technology could support business, an explanation with examples
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 Innovation based on the data - It takes a lot of time and efforts in order to
identify key areas that are growing for the experimentation and attempts in order to
innovate something. Big data methods can help with research and development
department that can lead to the innovation of new services and products (Grover, and
Kar, 2017).
 Flexible supply chain - Big data includes predetermined evaluation and it is
usually done in present time that helps in maintaining the global link of demand,
production, and distribution in order to operate these things smoothly. There are
various companies which are able to operate in effective and efficient supply chain
management.
 Privacy- It is very essential for both organization and consumers. By utilizing this
method of big data technology it plays a vital role in the development of organization
by protecting the data of their consumers. For instance, Marks and Spencer is a
multinational retailer that utilizes the technology of big data in order to keep the data
of their consumers secure.
References
Ashabi, A., Sahibuddin, S.B. and Haghighi, M.S., 2020, April. Big data: Current challenges
and future scope. In 2020 IEEE 10th Symposium on Computer Applications &
Industrial Electronics (ISCAIE) (pp. 131-134). IEEE.
Ghasemaghaei, M., 2020. The role of positive and negative valence factors on the impact of
bigness of data on big data analytics usage. International Journal of Information
Management, 50, pp.395-404.
Grover, P. and Kar, A.K., 2017. Big data analytics: A review on theoretical contributions and
pp.203-229.
Grover, P. and Kar, A.K., 2017. Big data analytics: A review on theoretical contributions and
tools used in literature. Global Journal of Flexible Systems Management, 18(3),
pp.203-229.
Ismail, A., Shehab, A. and El-Henawy, I.M., 2019. Healthcare analysis in smart big data
analytics: reviews, challenges and recommendations. In Security in Smart Cities:
Models, Applications, and Challenges (pp. 27-45). Springer, Cham.
Martin, M.E. and Schuurman, N., 2020. Social media big data acquisition and analysis for
qualitative GIScience: Challenges and opportunities. Annals of the American
Association of Geographers, 110(5), pp.1335-1352.
Patel, D., Shah, D. and Shah, M., 2020. The intertwine of brain and body: a quantitative
analysis on how big data influences the system of sports. Annals of Data
Science, 7(1), pp.1-16.
Sheeran, M. and Steele, R., 2017, October. A framework for big data technology in health
and healthcare. In 2017 IEEE 8th Annual Ubiquitous Computing, Electronics and
Mobile Communication Conference (UEMCON) (pp. 401-407). IEEE.
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Poster
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