Data Mining Applications and Challenges in Cloud Environment (SaaS)

This report delves into the applications of data mining, specifically within cloud computing environments, including Software as a Service (SaaS) models. It highlights the usefulness of data mining for various sectors, such as service providers and crime agencies. The report also discusses the challenges associated with implementing data mining in the cloud, such as managing large data volumes, data capture, searching, sharing, transmission, and analysis. It addresses other issues like contract terms with vendors, security concerns, dependencies on multiple systems, and the limitations of current data mining tools when dealing with Big Data. The report concludes by suggesting that further research is necessary to develop more efficient data mining tools to overcome these challenges and improve their application for Big Data and related fields.

Running Head: CLOUD COMPUTING
Data Mining
Name of the Student
Name of the University

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Data Mining Application and the Challenges in Implementing the Application
in Cloud Environment (SAAS)
Data Mining is defined as an effective tool that is used to analyze a piece of data based on
different perspectives as well as extract information from that piece of data. Data Mining is used
in Computational Process that discovers the pattern in a Sets of Large Data that has methods of
Database Systems, Machine Learning System and Artificial Intelligence. In the process of Data
Mining, the information is extracted from the set of data and it is use further with an
understandable transform structure [2]. The process also include the data in large amount were
new and hidden information are found through which the business can be improve. Data mining
is widely used in various fields and in different applications. One of the most popular
applications of data mining is cloud computing where it is used for classification and
categorization of data as well as finding data pattern correlations within the cloud.
Some of the common and real time application of data mining are as follows.
Service Provider: The companies of Mobile phone and the utilities industries uses Data
Mining to predict the churn when the customer leaves the company to get the broadband or gas
or phone through other provider. They assemble interactions to customer services, billing
information, visits to website to gain a probability score.
Crime Agencies: The prevention agencies use Data mining to spot the myraids of data to
deploy the police manpower.
In spite of all these applications, there are several challenges of application of data
mining in the cloud environment. These challenges are discussed as follows.

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 Data Capture and Storage
 Data Searching
 Data Sharing
 Data Transmission
 Data Curation
 Data Analysis
 Data Visualization
All these challenges arise from one common issue i.e. the enormous volume of data to be
handled in the cloud. While data mining is used in the cloud, it is often associated with Big Data
and hence, it needs to handle a huge amount of data [1]. This makes it extremely difficult to
perform any of the actions like capture, searching, sharing, transmission, analysis and others.
Some other challenges of data mining include:
Contract terms with the vendors: Contingency and SLA plan
Security: there is no control over the data for the company beyond the firewalls
From the company the data get transferred regularly to the cloud through the
Internet
Dependencies on multiple system: ISP uptime, Vendor server and more
Data mining is truly a very useful tool for information capture but it is evident that it is
not much suitable for use on Big Data owing to its enormous volume and the tool’s limited data
capturing capacity. Hence, further research activities are to be conducted in order to develop
more efficient data mining tool so that it can be more effectively applied for Big Data mining as
well as other similar applications.

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References
[1] Han, J., Pei, J. and Kamber, M., 2011. Data mining: concepts and techniques. Elsevier.
[2] Dillon, T., Wu, C. and Chang, E., 2010, April. Cloud computing: issues and challenges.
In Advanced Information Networking and Applications (AINA), 2010 24th IEEE
International Conference on (pp. 27-33). Ieee.