Business Management BMP4005: Big Data Analysis Report and Techniques

This report delves into the realm of big data analysis within the context of business management, specifically addressing the BMP4005 course. The content begins with an introduction to big data, elucidating its characteristics such as volume, variety, velocity, veracity, value, and variability. It then proceeds to outline the challenges encountered in big data analytics, encompassing data management complexities, talent gaps, data integration issues, and the extraction of actionable insights. Furthermore, the report details various techniques employed for analyzing big data, including A/B testing, classification, sentiment analysis, and social network analysis. The core of the report lies in demonstrating how big data technology supports businesses, with examples such as enhanced customer communication, product remanufacturing, risk analysis, data security, and revenue stream generation. The report concludes with a list of references and an appendix containing a poster summarizing the key concepts.

Business Management
BMP4005
Information Systems and Big Data Analysis
Poster and Summary Paper

Table of Content
Introduction......................................................................................................................3
Explain the big data and its characteristics.............................................................................3
Challenges of Big data Analytics.........................................................................................................4
Techniques which are available to analyse the Big data......................................................................4
Ways in which big data technology supports the business along with an example..............................5
References.............................................................................................................................................7
Appendix 1 : Poster...............................................................................................................................8

Introduction
There are various types of ways that are required to run the business effectively. There is a
team of managers that work on the process of the working of the business. It requires planning,
coordinating among the team members , analysing the working of the company and making layouts
for the operation of the business all this is know as the management done in the business. All this
can be done with the help of the technologies, like the information technologies such as software
and hardware. This summary discuss about the topic of Big data, explaining the topic along with its
characteristics. The challenges faced while using this for analysing, even the techniques used for
analysing are explained in the summary and also mentioned the big data technologies used to
support the business.
What is Big data?
It is data that has many varieties in the data, its increasing in the volume along with a lot of
velocity. Big data is huge in size, has more mixed sets of data from data sources that are new. There
is required of new technologies to analyse the data as the old version of the analysing the data is not
suitable as the data is huge enough and the traditional analysing data can not be used so there is a
need for a new and latest technologies.(Saggi, 2018. ) The data is kept in warehouse of data rather
than the the data base as the files are bigger in number. The velocity of the data is rising along with
the increase in the variety. This process is used in making decisions for the business, this even gives
the high level of the analytical insights and also provides business intelligence. This data analytical
technique is used in various fields such as medicine, gambling, agriculture and many more.
Characteristics of big data
There are five main characteristics of big data with one additional
 Volume: in this the count is large and in bulk which a company uses to analyse the data.
 Variety: there are different types of the big data analyse that is used by the business, it is
raw data, unfinished data and partially completed data.
 Veracity: this is amount of truthfulness in the data provided by the business organisation,
even the accuracy in the data which is mention in the data base.
 Value: the value of the data is the main source of the business, it leads to more effective
operation of the business. (Ardito, et.al., 2018)With the help of Big data there is proper
operation of the business

 Velocity: this is an important element as the speed matters in the operation of the business, it
mentions the time period and speed used to collect, store and manage the data, There is a
example such as sources from the social media, like the search engines, even the post of the
social handles.
 Variability: there are different ways in which the business collects, keeps and manage the
data to analyse. In this the main process is on the changes in the meaning of the major words
in the data, also the analyses of the text sentiments.
The Challenges of big data Analytical
There are majorly five challenges that are faced in the process of big data analytical
 Uncertainty of Data management landscape: as there is rapidly increase in the big data
and so are the new companies and organisations being established which require to use new
techniques and technologies . There is a need to be updated about the new techniques in the
market which will be best suitable for the particular company. (Maroufkhani, et.al., 2020.)
 The big data talent gap: this big data is expanding continuously in every filed as it is very
useful in understanding the data of each area with complexity and indicates the nature of the
data.
 Getting data into the big data platform: it is required to keep all the data in a proper
systematic manner, as it will take easier time to keep the data available to the company. The
data should be quickly approachable.
 Need for synchronization across data sources: with a huge amount of files and data there
is a need to have set of data that can be helpful to have them in an corporate analytical
platform.
 Getting important insights through the use of big data analytics: it is required that the
information about the data should reach to the right department without mixing the data.
There is a challenge in doing this as the data is big, so it is difficult that the data gets stored
in the right area. (Kolisetty,., 2020.)
Techniques available to analyse the big data
There are few techniques that are used now days to analyse the big data and they are
 A/B Testing: there is a comparison between the main group that controls the variety with
the a specific to access the way in which the major variable will be changed. Basic motive of
this is to compare the variables among each other and it lastly offer the chooses that are best
for the big data.

 Classification: the classification of the data is helpful in sorting the information in a way
that becomes easy to search ad find out the information in a quick manner. All the
techniques used are supervised learning, this even is used in making decisions for the
business.
 Sentiment analysis: this is used to understand the requirement of the customers and the
emotions with the content of data and it is analysing the data in a way in which many
features are studied according to the brand, service and even the commodity. It is required to
determine the sentiments of the researcher which include the emotion of the motivator and
publisher and al this helps in the building the sentiments of the people involved in the same
data. (Aljehane, N., 2020, )
 Social network analysis: it is required to maintain a cultural and social bond with the clients
and the customers. This data collection was firstly used by the telecommunication and
further it was even taken in use by the social scientist as to understand the concept of the
social culture. It is used to determine and study the relationship among the people of
different places and areas.
How Big Data technology could support business, an explanation with examples
The big data technology supports the business in various ways which are stated below as:
 Communicating with consumers: Customers are smarter and understand their priorities
according to current scenarios. They explore and explore everything around them before
making a purchase. In addition, she communicates with business organizations through
various social media platforms. Companies can use big data to reach such customers and
interact with them to learn about their needs and desires. Companies need to treat their
customers the way they want, as if the market is very competitive. Example: A customer
enters a bank. When he enters the bank, his profile and his likes and dislikes are validated
with big data. This allows the clerk to gain knowledge about the customer's preferences and
use it to provide advice on related products or services to the customer.
 Product re-manufacturing: Big data helps us understand customer needs and wants. We
have a feedback system that helps our customers update the features, quality and finishes
they want in their products. The company learns about this feedback through big data
analysis and makes relevant changes to the product. Example: After delivery of the product,
the company asks for feedback with several questions such as: "Do you like the quality of
the product? Was the item delivered on time? How high would you rate product quality out
of 5? and want to buy more products from us?
 Conducting a risk analysis: This is an analysis of potential company risks or issues that

could adversely affect the organization's operations. Big data analytics enable companies to
analyse and scan social media feeds and newspaper coverage to help identify current
marketing scenarios It helps companies to know their competition in the market, so they can
stay up to date with the latest trends and developments in the industry to beat the
competition.(Gupta,., 2019. )
 Data Security: Businesses can use big data analytics to find the entire database within an
organization. It allows companies to analyse all kinds of insider threats to remove or
remediate those threats and keep their critical information safe. Therefore, big data analytics
helps data security
 Create a new revenue stream: Big data helps businesses increase their annual sales by
providing all the information about their customers' needs, desires, desires, and more.
Example: Like Google, by collecting continuous feedback from customers and suggesting
search options, businesses can generate more sales.
References

Books and Journals
Saggi, M.K. and Jain, S., 2018. A survey towards an integration of big data analytics to big insights
for value-creation. Information Processing & Management, 54(5), pp.758-790.
Ardito, L., Scuotto, V., Del Giudice, M. and Petruzzelli, A.M., 2018. A bibliometric analysis of
research on Big Data analytics for business and management. Management Decision.
Maroufkhani, P., Tseng, M.L., Iranmanesh, M., Ismail, W.K.W. and Khalid, H., 2020. Big data
analytics adoption: Determinants and performances among small to medium-sized
enterprises. International Journal of Information Management,54, p.102190.
Kolisetty, V.V. and Rajput, D.S., 2020. A review on the significance of machine learning for data
analysis in big data. Jordanian Journal of Computers and Information Technology (JJCIT),
6(01), pp.155-171.
Aljehane, N., 2020, September. Big data analytics: challenges and opportunities. I 2020
international conference on computing and information technology (ICCIT-1441)(pp. 1-4).
IEEE.
Gupta, D. and Rani, R., 2019. A study of big data evolution and research challenges. Journal of
information science,45(3), pp.322-340.
Appendix: Poster

Appendix Poster