Data Mining Report: Exploring Data Mining in Software Development

This report, prepared by a software developer, focuses on the application of data mining in the context of programming languages such as Angular, Dot net, Azure, and SQL. It discusses the importance of data mining, its techniques, and its applications in the software development field, including fraud detection, customer relationship management, and financial banking. The report covers the author's learning experience with data mining, highlighting the use of statistical methods, machine learning, and database systems to extract and analyze data. It emphasizes the benefits of data mining in preprocessing data, visualization, database management, and artificial intelligence. The report also explores different data mining methods, common task classes, and the role of data mining in decision-making processes, emphasizing the importance of understanding database concepts like the ER model and SQL. The author reflects on the ease of learning data mining given their existing SQL knowledge and concludes by emphasizing the relevance of data mining in today's data-driven world.

Running head: DATA MINING
DATA MINING
Name of the Student
Name of the University
Author Note

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Table of Contents
Introduction:...............................................................................................................................2
Discussions.................................................................................................................................2
Conclusion..................................................................................................................................3
References..................................................................................................................................4

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Introduction:
The report deals with the four programming language courses Angular, Dot net,
Azure and SQL. I am working as a software developer and using the above programming
languages for the development of software. The report discusses about the specific
knowledge and the theories that can be identified from the data mining courses. Data mining
is a very important course and everyone does this course these days. Data mining has huge
amounts of applications in today’s life such as fraud detection, customer-relationship
management, financial banking and many more (Buczak, & Guven,2015).
Discussions
I have learnt that data mining is the procedure of discovering patterns in large number
of data sets that involves methods such as statistics, machine learning and database systems. I
am learning from data mining that it is used to withdraw information’s from large data sets
and change them into understandable structures. Data mining is helping me to learn pre-
processing of data, visualization, database and aspects of data management. It is helping me
to learn artificial intelligence. Data mining is also helping me to learn processing of huge
amounts of information that includes collection, extraction, warehousing, analysis of data and
statistics (Kim et al., 2016). Data mining is helping me to learn the techniques of database
such as the spatial indices. There are also different types of data mining methods that i am
learning from the courses of data mining. The data mining methods are data snooping and
data fishing. There are six common classes of task that i am learning from the data-mining
course. The six common classes are summarization of data, regression analysis, and
classification of data, clustering, anomaly detection and association rule learning (García,
Luengo & Herrera, 2015). These tasks are helping me to learn to extract information from
large number of data sets. The course of data mining is helping me in my work environment a

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lot. It is helping me to extract huge amounts of information from the data sets and then is
used for making the decisions from the data sets or checks the accuracy of the data’s. Data
mining is a part of artificial intelligence and artificial intelligence is helping me to develop
characteristics in the softwares (Witten et al., 2016). Data mining is helping me to make
decisions using the models that are available in data mining courses. Before learning data
mining one should first understand the concepts of database such as the ER model, schema,
and Structured Query language and the basic concepts of data warehousing. As, i knew SQL
for the development of software, learning data mining was not tough.
Conclusion
I am a software developer working on languages such as Azure, SQl, Angular and Dot
net. This goal of the report is to learn data mining from its knowledge areas and the courses
that are available. Data mining has helped me a lot in my work environment and in my work
that i am doing. As, i know the structured query language, it was easy for me learn data
mining from its courses. Data mining is an important course in today’s life as everything on
the internet are either based on data mining or machine learning.

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References
Buczak, A. L., & Guven, E. (2015). A survey of data mining and machine learning methods
for cyber security intrusion detection. IEEE Communications Surveys &
Tutorials, 18(2), 1153-1176.
García, S., Luengo, J., & Herrera, F. (2015). Data preprocessing in data mining (pp. 59-139).
New York: Springer.
Kim, M., Zimmermann, T., DeLine, R., & Begel, A. (2016, May). The emerging role of data
scientists on software development teams. In Proceedings of the 38th International
Conference on Software Engineering (pp. 96-107). ACM.
Moeyersoms, J., de Fortuny, E. J., Dejaeger, K., Baesens, B., & Martens, D. (2015).
Comprehensible software fault and effort prediction: A data mining approach. Journal
of Systems and Software, 100, 80-90.
Tan, P. N. (2018). Introduction to data mining. Pearson Education India.
Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016). Data Mining: Practical machine
learning tools and techniques. Morgan Kaufmann.