Big Data and its Challenges: A Reflection on Internship Experience

This report reflects on the characteristics, challenges, and technology supporting big data in business. It also discusses the impact of big data on operational efficiency and the challenges faced by organizations in analyzing big data.

Reflection on my internship
experience

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................3
MAIN BODY..................................................................................................................................3
Big data and its characteristics....................................................................................................3
Challenges of the big data analytics............................................................................................4
Big Data Technology supporting business..................................................................................5
CONCLUSION................................................................................................................................6
REFERENCES................................................................................................................................8

INTRODUCTION
Big is data is also considered to be the data that contains a greater variety of information
that arrives in increasing the volumes and more velocity. This project has been able to identify
the different type of data and understand the various principles, challenge and techniques of the
big data analysis. This project has been able to influence the Big Data that can be used for the
supporting the business objectives and functions.
MAIN BODY
Big data and its characteristics
Big data is that data that contain great variety of increased volume, arriving with high
velocity of information. This is also considered to collection data that is generate form different
sources that are differentiated in the following categories,
Volume:
This is also considered to be the factor that is able to influence the size and its amount of
the big data which is able to be managed and analysed according towards the understanding (Cui,
Kara and Chan, 2020).
Value:
Value is the most important characteristics of the organization which is also considered to
be very important for the development of the insights which is relevant for the discovery of
pattern a recognition of the lead that is able to effect the operations. The stronger the bond
between the customer relationship management and the other clear quantifiable business
benefits. The focus of the organization has been towards the factor which are influences for the
management of the operational growth.
Variety
Increase level of variety of the big data is also considered to be the factor that influences
the differences towards the structuring of the data and also the differentiates it from the raw data.
Velocity:

The speed at which the companies are receiving, storing and managing the data is
considered to be the factor that is able to influence the social media posts and also influence the
search queries and influences the received within the day of the other units of the time
(Ghasemaghaei and Calic, 2020).
Veracity:
The truth of the accuracy is also considered to be the factor that is able to inform the
assets which is able to determine that executive level confidence. This is considered to be the
factor that is able to influence the change nature of the market.
Challenges of the big data analytics
The different challenges that businesses face for the decision making of an organization are,
Lack of knowledge Professionals
To be able to run the different modern technologies and the large data tools, companies
need skilled data professionals. These professionals will be including the data scientists, data
analysts and data engineers to work with the tools and make sense of the giant data sets. It has
been considered that the Big Data challenges which the company has been facing are considered
to be the factor that influences the ways in which the business is able to handle the tools that
have evolved rapidly but in most cases the professionals do not take such actions. These actions
are considered to be the factor increases the gap that is there in the different forms of data.
Lack of proper understanding of Massive Data
Companies are considered to fail due to high level of initiative that they have to take
because of the large data sizes. Employees might not be able to help the storage, processing,
importance and sources. It is considered to be the factor which influences the data that tkes place
when the business has to paint a picture. The employees are able to understand that the
knowledge of storage when they have to keep the sensitive data intact for being able to store the
data for retrieving them at the basis of the analysing the factor that is considered to be very
important for storing the backup of the sensitive data. It has also been considered to be the factor
that influences that data bases which is properly se for the purpose of the storage. This is very
important data which is required for the retrieving the easy information from the big data.
Data Growth Issues
The issues that are present with the challenges of the big data is that these huge sets of
information have been considered to be cantered in the data base of the companies towards the

increasingly rapid sets of growth. This is also considered to be the data set which is unstructured
and comes from the documents, videos, audio, text files and other sources. This has also been
considered to be factor that is able influence the database which is the factor that bring forward
the organizational growth. Analysation for the data and their fuels of the digital business face this
issue the most as the growth of the data. Companies are able to influence that large sets of data
which is able to compress the tiring and deduplication (Javed Awan and et.al., 2021). The
compression of the employed or the reduced number of data is considered to be the reason for
the influence of the data from the known sets of data.
Confusion while Big Data Tool selection
The main confusion that the Big Data tool section is that due to the increased size of the
Big Data the selection of the organization has been considered to be a difficult choice. Due to the
increase size of the data the factors which influences the choice of the data tool also starts
varying. It can be said that the due to the difficult decisions which were made for the selection of
the inappropriate technology increase the effort, time, money and also hours which are spend in
the organization.
Integrating Data from a Spread of Sources
Due to the integration of the spread of the sources the different sources such as the social
media pages, ERP applications, customer logs, financial report, emails and presentation of the
reports are considered to be created by the employees. It has been considered to be the factor that
influences the data integration process which is very important for the analysation of the
reporting and business intelligence which is not perfect.
Securing Data
Securing of the data that is gathered from the huge sets of knowledge is considered to be
the facto that is able to challenge a large and massive data. This is also considered to be the
factor which influences the storing and analysing of the data sets which is able push the data
security for the later stages. It is considered that the sensibility of the unprotected data can be the
reason for repositories and also influences the breeding grounds for the malicious hackers. It is
also considered for the companies for losing the essential information.
Big Data Technology supporting business
The big technology has been considered to be supporting the business with different ways in
which the organization,

Quality:
Big data has been considered to be the factor that has been considered to be the key factor
that is able to seek some sort of competitive advantage which helps in better and more precise
target marketing. Through the advanced data analytics and more improved decision making the
offers made to eh quality of the products and the services is affected. It is able to facilitate the
monetization for providing a better understanding of the client needs for the personalization for
the focusing that is approach for cutting the time which is able to increase the efficiency of the
business proposals. This is also considered to be the factor that is able to influence the
approaches that impacts the increase in the time and efficiency of the business processes. The
adoption of big data results in a higher quality of the products, enhanced customer’s experiences
for the satisfaction from the clients.
Cost:
The data driven AI projects are commonly developed for the sake of workflow
automation benefits. It has been considered to be the factor that is able to influence the benefits
(Reddy and et.al., 2020). The focus of the human experts and the factors that allow them to add
value to the business goals are able to help the business reduce the costs for improving the
efficiency of the existing business process.
Analytics:
The predictions of the ways in which the Big Data allows the business to analyse the
pattern in the organization is considered to be the process which is able to influence the ways in
which data visualization and its perks are influences by the use of big data. The bigger the
picture that sis driven by the help of most important questions that influences the factors that is
able to help in giving the data a permanent motion.
CONCLUSION
From the above report it can be concluded that the use of Big Data can be very essential for
an organization as it increases its operational efficiency. This report was able to analyse the
characteristics of Big Data. In this report the different challenges faced by the techniques that are
currently available for the Big Data analysis was found. Big data was also considered to be the
supporting factor that influences the business with the different types of support.

REFERENCES
Books and Journals
Cui, Y., Kara, S. and Chan, K.C., 2020. Manufacturing big data ecosystem: A systematic
literature review. Robotics and computer-integrated Manufacturing. 62. p.101861.
Ghasemaghaei, M. and Calic, G., 2020. Assessing the impact of big data on firm innovation
performance: Big data is not always better data. Journal of Business Research. 108.
pp.147-162.
Javed Awan, M., and et.al., 2021. A big data approach to black friday sales. MJ Awan, M.
Shafry, H. Nobanee, A. Yasin, OI Khalaf et al.," A big data approach to black friday
sales," Intelligent Automation & Soft Computing. 27(3). pp.785-797.
Reddy, G. T., and et.al., 2020. Analysis of dimensionality reduction techniques on big data.
IEEE Access. 8. pp.54776-54788.
Online
Top 6 Big Data Challenges and Solutions to Overcome, 2021[Online]. Available through: <
https://www.xenonstack.com/insights/big-data-challenges>
[Online]. Available through: <>