Business Intelligence

6/1/2020 Originality Report

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SafeAssign Originality Report Summer 2020 - Business Intelligence (ITS-531-40)(ITS-531-41) - COM… • Week 4: Assignment Homework 4

%53Total Score: High riskAvinash Kustagi Submission UUID: a477046b-f773-05f5-3f16-5ee6e34a32d9

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1 Highest Match

53 % Homework assignment 4.docx

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05/31/20 12:09 AM EDT

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596 Highest: Homework assignment 4.docx

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Word Count: 596 Homework assignment 4.docx

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1 Student paper

6/1/2020 Originality Report

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Running head: Data MINING 1

Data MINING 8

Data Mining

Student: Avinash Kustagi

University of Cumberlands

Course Name: Business Intelligence

Course number: ITS-531

Professor: Dr. Abiodun Adeleke

05/29/2020

Data mining can be explained as the method to interpret information and hypothesis from large knowledge and data collections like databases or data warehouses. Data mining popularity is increasing rapidly right now in the world. It is slowly becoming one of the most desired fields of work in the world right now. Data plays a very big role in developing and shaping a business. It is because of Data mining that an organization comes to know more about what the market has demand for and what their customers prefer and what they absolutely dislike. Data mining has proven to be extremely helpful in making valuable and important business decisions. As described in the article” Business data mining — a machine learning perspective”, data mining has become an integral part of business development (Bose & Mahapatra, 2001). Data mining has several applications in different fields of life. It is used in the field of finance, television industry, education, retail industry, and telecommunication industry. Data mining is very valuable in the field of finance. Data mining help in data analysis to find a result in loan prediction. It gives an analysis of the customer’s credit history and fraud detection (Valcheva, n.d.). It also assists in determining the previous money laundering trends and deduces a conclusion about any unusual patterns in a credit history. It also assists in helping develop targeted marketing. In the field of finance, data mining and analysis helps in deducing conclusion results from the previous trend in markets to determine what fiscal products the customer will be interested in coming times. Through this strategy, the product development team of several financial institutions decide the new products and the conjoining discounts, offers, and packages on these products. Data mining also has a tremendous application in the television and radio industry. Television shows producers use the process of data mining to generate predictions about the general trend in storylines that the audience is interested in watching. It shows a general pattern of behavior of the market and customers and helps a

business to make decisions about their market value and how to approach their businesses (Apte, Liu, Pednault, & Smyth, 2002). They also use the data mining procedure to generate advertisements and what ads go with what shows the best. Television and Radio marketing team develop customized promotional strategies for their customers using the help of data mining. Data mining also helps television and movie studio executives to conclude results from an extremely large inventory of content and story writing to fact check certain stories in their shows and also help them to protect from any future copyright infringement case they could face. Some executives also use data mining to conclude results from surveys of how the audience is reacting to certain risky stories. It’s important in the entertainment industry to know about what was successful in the past, what the people like, and how people react to certain scenarios, and all such is made possible through the help of data mining.

References

Apte, C., Liu, B., Pednault, E., & Smyth, P. (2002). Business applications of data mining. Communications of the ACM Volume 45, Issue 8. Bose, I., &

Mahapatra, R. (2001). Business data mining — a machine learning perspective. Information & Management Volume 39, Issue 3, 211-225. Valcheva, S. (n.d.). 7

Data Mining Applications And Examples You Should Know. Retrieved from Intellspot: http://www.intellspot.com/data-mining-applications/

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6/1/2020 Originality Report

https://ucumberlands.blackboard.com/webapps/mdb-sa-BB5a31b16bb2c48/originalityReport/ultra?attemptId=81c044c4-395e-4a6c-a5a6-511adc5035… 3/3

Student paper 91%

Student paper 100%

Student paper 96%

Student paper 100%

Student paper 100%

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Student paper

05/29/2020 Data mining can be explained as the method to interpret information and hypothesis from large knowledge and data collections like databases or data warehouses. Data mining popularity is increasing rapidly right now in the world. It is slowly becoming one of the most desired fields of work in the world right now.

Original source

03/29/2020 Data mining can be explained as the method to interpret information and hypothesis from large knowledge and data collections like databases or data warehouses Data mining popularity is increasing rapidly right now in the world It is slowly becoming one of the most desired fields of work in the world right now

1

Student paper

Data plays a very big role in developing and shaping a business. It is because of Data mining that an organization comes to know more about what the market has demand for and what their customers prefer and what they absolutely dislike. Data mining has proven to be extremely helpful in making valuable and important business decisions. As described in the article” Business data mining — a machine learning perspective”, data mining has become an integral part of business development (Bose & Mahapatra, 2001).

Original source

Data plays a very big role in developing and shaping a business It is because of Data mining that an organization comes to know more about what the market has demand for and what their customers prefer and what they absolutely dislike Data mining has proven to be extremely helpful in making valuable and important business decisions As described in the article” Business data mining — a machine learning perspective,” data mining has become an integral part of business development (Bose & Mahapatra, 2001)

1

Student paper

It shows a general pattern of behavior of the market and customers and helps a business to make decisions about their market value and how to approach their businesses (Apte, Liu, Pednault, & Smyth, 2002).

Original source

It shows a general pattern of behavior of the market and customers and helps businesses to make decisions about their market value and how to approach their businesses (Apte, Liu, Pednault, & Smyth, 2002)

1

Student paper

Apte, C., Liu, B., Pednault, E., & Smyth, P.

Original source

Apte, C., Liu, B., Pednault, E., & Smyth, P

1

Student paper

Business applications of data mining. Communications of the ACM Volume 45, Issue 8. Bose, I., & Mahapatra, R.

Original source

Business applications of data mining Communications of the ACM Volume 45, Issue 8 Bose, I., & Mahapatra, R

1

Student paper

Business data mining — a machine learning perspective. Information & Management Volume 39, Issue 3, 211- 225.

Original source

Business data mining — a machine learning perspective Information & Management Volume 39, Issue 3, 211- 225