A Comparative Study of Data Mining Tools and Techniques for Business Intelligence

Ramesh, Gowtham; Kanth, T. V. Rajini; Vasumathi, D.

doi:10.1007/978-981-13-8253-6_15

Cited by 3 publications

(2 citation statements)

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“…"Classification is the most deliberate and generally practiced supervised learning data mining task" (Wael M. S. Yafooz, 2020). It identifies which set of groups a new data belongs to, it helps enhance business intelligence taking decisions (G. S. Ramesh, 2020). Classification is a two step process, where in the first step the training set is outlining the training set data within predefined groups using extraction, while the second step using the outline to classify and new data introduced and might as well extract more authentic classification rules.…”

Section: Classificationmentioning

confidence: 99%

“…Naive Bayes can estimate unfamiliar limited anticipations to recognize groups, its known to deliver a great successful results in different Fields such as banking, marketing, medical-diagnosis and many more. On the other hand Random Forest can achieve building efficiency of performance and decreasing variance which makes it an excellent training model (Ramesh, 2020;Oudat, Ali, & Qeshta, 2021 ;.…”

Section: Classificationmentioning

confidence: 99%

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Business Intelligence and Data Mining: Opportunities and Future

2021

EJBM

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In the business world, endless streams of information "data" are needed in order to properly initiate the process of an effective business by analyzing different needs that the service has in relation to the needs of the end-customer, by anticipating these needs, the aim of any service creation is to meet customer requirements. In the recent years business intelligence (BI) been an interesting topic in almost every field. Likewise data mining which is a good solution in business intelligence matter, as for discussion, application and business domain. There are various attempts to detect the characteristics of services that are important to the acceptance of the service offered. The quest for attributes that satisfy and excite the consumer is possible through the use of various technological research approaches, but the efforts are enormous. The business is able to collect customer data in a more reliable and simpler way with the use of 'Smart Systems,' which are Information and Communication Technology (ICT) enabled services. The use of data mining and business intelligence to enhance the reversal of consumer needs when designing collection techniques is defined in this paper. The main purpose of this study is to define the importance of business intelligence with it features, how data mining works and some data mining techniques discussed in brief, in addition to exploring the future and opportunities of Business Intelligence and Data Mining.

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Section: Classificationmentioning

confidence: 99%

Section: Classificationmentioning

confidence: 99%