Information Systems and Big Data Analysis

This report discusses the concept and characteristics of Big Data, the issues faced in Big Data analysis, and the techniques used for solving them. It also explains how Big Data technology supports businesses with examples. The report includes references for further reading.

Information Systems and
Big Data Analysis

Contents
Contents...........................................................................................................................................2
INTRODUCTION...........................................................................................................................1
MAIN BODY..................................................................................................................................1
Identify the big data and its concept............................................................................................1
Discuss the issues that has faced in big data and methods or techniques used for solving the
problems......................................................................................................................................2
Explain Big Data Technology Supporting Businesses with certain examples............................3
CONCLUSION................................................................................................................................4
Poster...............................................................................................................................................5
REFERENCES................................................................................................................................6

INTRODUCTION
An organization collects the data from organized, semi-organized and the unorganized
firms which can be pull out for all the data and information and also, technological projects
anticipatory model and other advanced analytical techniques and methods can be used as big
data. In this report, it includes the definition and characteristics of the big data (Albqowr,
Alsharairi and Alsoussi, 2022). It helps to faced the challenges with the help of big data and the
techniques that are usable in present for this analysis.
MAIN BODY
Identify the big data and its concept
Big data helps to gather all the data which is vital in quantity. They have efficient power
to develop speedily with the given time period. It has large capability of data in size. Instead of
this, there is no conventional data techniques and tools. They can assemble it or function it in
manner way with full efficiency. These type of applications or methods have become casual
element of the data management framework in entities. Which helps in using of big data
analytics. To get the latest version of their operations, the business firms utilize the big data
technologies. It aids to make the better availability and do changes in their services regarding
customer (Dominguez and et al., 2021). It promotes the marketing activities that comes positive
impact in results i.e. it enhance the revenue as well as profit of the business entities.
These technologies consists number of advantages with it:
 Better customer and consumer service has been provided.
 It helps to enhance the efficiency of the function of the business.
 Decide the risk of the goods and services of the company. The organization can use extrinsic administrative units or services during the decision
making process.
Features of big data: It is an accumulation of data from the several different sources which is
wide and usually, it elaborate its five characteristics.
1. Volume: It involves the incredible quantity of information which has been made with the
help of social media and related resources. The name of big data is incidental to the size
that is very vast or tremendous. To determine the value of data, the size plays a important
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role. It totally up on the data's volume. It should be consider into mind during the dealing
time with these type of solutions.
2. Variety: It consists heterogeneous sources as well as quality of data. Both the firms are
included organized or unorganized. In the beginning days, mostly applications were
databases and spreadsheets. It is the only source which is considered. It is created in
several different varieties. In today's scenario, photography and videography are useful
on the basis of analysis of application (Hammou, Lahcen and Mouline, 2020).
3. Velocity: It refers to the time period of the speed of the data that shows the time i.e. how
much time has been taken by the data to processed for the purpose of catching the
demands and decides the data potentially. It plays huge role to comparing the other
features of the big data. On demanding time, it make sure the availability of the data.
4. Variability: It involves the statical distribution i.e. the non- similarity that can be
presented through the data in many cases, so managing the data in manner way company
has to impose strict processors.
5. Value: It is the crucial part of the big data technology. It consists the amount of data that
is necessary to be preserved, progressed and evaluate to figure out and understand the
insights.
Discuss the issues that has faced in big data and methods or techniques used for solving the
problems
In this digital scenario, for the efficient decision making the business utilized this
technologies for the purpose of growth of the firms or companies. It also aids to enhance the
productivity, taking healthier predictions, control and monitor the performance, adopt
competitive benefit over its rivalries.
Major problems suffered by using these Big day techniques are discussed below: Incapable to furnish new insights on time: In order to take better and improved
organization decision analytics used by the business. But it can be observed that the data
or information which is provided by the new techniques or system matches the earlier
information or not (Hassanien, Dey and Borra, 2018). It can be happened due to the
inadequacy of the data with the help of approaches of traditional of a new system or
application.
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 Incorrect analytics:This is the important issue suffered by the business and it requires the
special and faster attention of the organization management for the purpose of resolving
the problems. Inadequacy of the data analytics can be occurred due to the improper or
wrong data quality that is not completed or also contains lots of faults and errors due the
problem in system or application. Complications in utilization of data analytics: Business finds the difficulties in this
system to get the solution from the data or information while the processor of using the
data analytics become complex. Due to the deficiencies of the proper and exact technical
knowledge complexity rises (Morota and et al., 2018).
Techniques of evaluating Big data
 Machine learning: It contains software system that can be learned from the data. It
furnishes the ability to hold without being specify programmed and concentrates on build
the project which is based on the known properties and that enwrapped from the sets of
guiding data. It assists in distinguishing amongst the junk and non junk emails and create
ideas or suggestions that depends on the given components.
 Regression Analysis: It considers with inventing the some autonomous variable like how
it determine or affects a dependent variable (Nayak, Bhattacharyya and Krishnamoorthy,
2019). It presents that how much the value of the reliant variable when the
unconventional variable is abnormal. It works better with the repetitive quantitative data
or information like mass or age group.
Explain Big Data Technology Supporting Businesses with certain examples.
By utilising Big data, businesses are able to analyse the business analytics and build up
reliable customers relations with a long term objective. It also helps the industries in creating
newly identified contents, services and products. Big data technology can provide assistance
business concerns in various ways as discussed below:
Making better business decisions: Big data helps the business concerns in fetching
smarter decisions which are backed up by data and not simply on the basis of premises.
Individuals utilising the data of the organisation across the globe have the quality to
analyse and enquire the data so that they are able to answer their customer's most critical
business inquiries. This organisation's wide formulation to data is known as data
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democratisation (Vo and et.al., 2019). Walmart is an outstanding illustration of this data
democratisation. Importantly, Walmart provides its people to conceptualisation to data in
a well organised way assuring that people who are not known of the technology do not
get soak up by data and can easily find the answer they want.
Delivering Smarter services or products: When an administration come to know about
its customers, it begins with the delivery smarter or appropriate commodities or services
for its customers which accomplish their needs entirely and fulfils them to the possible
length. Royal Bank of Scotland (RBS) is a great illustration of an administration utilising
Big Data to present improved service to its customers (Queiroz and Telles, 2018). RBS is
opening to assist the prospective of this knowledge to revise and amend its efficiency so
that it can fit within its customer wants or requirements.
Improving business operations:The outgrowth in automation is backed up by Big Data.
Robotics and high technology may be obsolete in manufacturing industry lines. But,
increasingly, various business aspects and dealings are becoming highly efficient,
impelling and machine-controlled (Zhao, Xu and Wang, 2019). PeopleDoc, a HR
software establishment, that has launched a Robotic Process Automation platform, which
functions likewise the existing system of the organisation and comprehend for the process
or events which can be automatize.
Creating an Income: Big Data does not only relates to ascending processes and
assumptions, or knowing more relating to its customer's information can be procedures
and conclusions, or understanding more about customer’s data can be monetize to
promote or make an auxiliary income stream. American Express is creating income by
the assistance of Big Data technology.
CONCLUSION
As per the above report, there has been concluded that Big data technology aids the
organization along with suffering several issues and problems and giving the methods or
techniques to suffer those limitations or issues and assist in the growth or profitability of the
business.
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Poster
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REFERENCES
Books and Journals:
Albqowr, A., Alsharairi, M. and Alsoussi, A., 2022. Big data analytics in supply chain
management: a systematic literature review. VINE Journal of Information and
Knowledge Management Systems.
Dominguez and et al., 2021. Improving emergency response operations in maritime accidents
using social media with big data analytics: a case study of the MV Wakashio disaster.
International Journal of Operations & Production Management.
Hammou, B.A., Lahcen, A.A. and Mouline, S., 2020. Towards a real-time processing framework
based on improved distributed recurrent neural network variants with fastText for social
big data analytics. Information Processing & Management, 57(1). p.102122.
Hassanien, A.E., Dey, N. and Borra, S. eds., 2018. Medical Big Data and internet of medical
things: Advances, challenges and applications.
Morota and et al., 2018. Big data analytics and precision animal agriculture symposium: Machine
learning and data mining advance predictive big data analysis in precision animal
agriculture. Journal of animal science, 96(4), pp.1540-1550.
Nayak, B., Bhattacharyya, S.S. and Krishnamoorthy, B., 2019. Integrating wearable technology
products and big data analytics in business strategy: A study of health insurance firms.
Journal of Systems and Information Technology.
Queiroz, M.M. and Telles, R., 2018. Big data analytics in supply chain and logistics: an empirical
approach. The International Journal of Logistics Management.
Shah, T.R., 2022. Can big data analytics help organisations achieve sustainable competitive
advantage? A developmental enquiry. Technology in Society, 68. p.101801.
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