Machine Learning Algorithm for Online Big Data Analytics Literature Review 2022

RESEARCH PROPOSAL 0
Machine Learning
Algorithm for Online
Big Data Analytics

RESEARCH PROPOSAL 1
Literature review
Big data is an advanced computing technology which is able to handle and
manage a large amount of data effectively. In this generation, many
business communities are using big data analytics for integrating and
analyze the collected data effectively. Machine learning is an algorithm that
helps the companies for solving complex situations through programming
and it can be used in the big data analytics for enhancing business process
effectively. The key purpose behind the literature review is to improve the
effectiveness of machine learning techniques and examine the findings of
the previous articles based on the big data analytics and machine
knowledge.
Al-Jarrah, et al., (2015) identified big data is defined as an approach which
is used for a larger transfer of skills and data from one system to another
[1]. It has potential for handling both semi-structured and structured data in
the companies and provides a platform to evaluate or analyze the gathered
information in less time. Machine knowledge is a part of AI that helps the
companies for connecting human things with physical devices and networks
and solves complex tasks in less time. It is identified that big data analytics
contains extracting effective information from the obtained data by
developing a possible relation with the various data.
Machine learning is able to manage big data effectively and provide a
platform to connect computing devices with human things. Chen, et al.,
(2017) identified that while using big data analytics the companies should
focus on the major three characteristics including volume, velocity and
variety and use effective techniques for enhancing the performance of
machine learning programs [2]. It is true that the utilization of big data
analytics may help the companies for improving business process and
machine learning has provided better impacts and a wide range of benefits
to the business communities. In order to exchange or transfer a large

RESEARCH PROPOSAL 2
amount of data sets the companies to require an automated system that
leads to machine learning systems.
Using the concept of machine learning the companies can easily transfer
large data from one device to other system and big data analytics can
provide better outcomes to the management. According to Fan, and Bifet,
(2013) there are major two challenges associated with the machine learning
programs for big data such as security and configuration of the networks
[3]. It is recognized that safety is a key issue linked with machine learning
by which the companies can hurt from records breach and security attacks.
For enhancing the privacy of data, the companies should implement
encryption techniques that convert the data into a form of code which
cannot be detected by the attackers without including private key [8].
It is suggested that companies can use land utilization and land
classification approach in order to solve challenges and issues associated
with machine learning and big data analytics. With the help of these
approaches the companies can predict, cluster and manage the
effectiveness of the machine learning programs and evaluate collected data
effectively. L’heureux, et al., (2017) supported this points and identified that
machine learning requires a platform to handle and identify the risk factors
and land classification in the best approach that may be utilized for
improving the performance of machine learning in the area of big data [4].
As compared with the previous papers this article provided depth
examination about machine learning and also provided effective strategies
for solving challenges occurred in the big data [9]. It is examined that the
utilization of effective computing networks and devices can lead to the
performance of big data analytics and reduces data integration issues. From
recent article provided by Landset, et al., (2015) argued that big data
analytics is capable risk management and calculate potential risks and