Current Issue

Volume 6, Number 4 / December issue 2020
Badriah Muteb Al-Otaibi
A survey study on data mining and its various important tools and applications

With the presence of large amounts of data stored in databases and data stores, the need to develop powerful tools for analyzing data and extracting information and knowledge from it has increased. Thus, the need emerged for what is called data mining as a technology aiming at extracting knowledge from huge amounts of data. Therefore, this current study aimed at clarifying the role of data mining methods in increasing the efficiency and effectiveness of the quality of the review process since it is an advanced method that can be very beneficial. This paper tries to clarify the nature of the data mining method and the dynamics of its work, as well as explaining the need to apply the data mining method and its importance in increasing the efficiency, effectiveness, and quality of the review process in many important applications. To achieve this goal, the researcher has used the critical evaluation method by reviewing the theoretical literature and previous studies related to the topic of multiple applications of data mining in several fields such as health, education, trade and economics, with the aim of bridging the gap between the previous studies and the practical applications of data mining. The study aims at identifying the objectives that previous studies sought, the results and recommendations that they reached, and their points of agreement and disagreement.
The study reached several conclusions including the fact that the data analysis technique is based on analyzing a huge amount of data and information to create a logical relationship, which makes it easier for decision makers in various institutions to make critical decisions about their institutions. Moreover, data mining technology also increases the efficiency and effectiveness of the quality of the data review process. The classification technology is considered one of the methods of data purification that can be relied upon in the educational field. In addition, the algorithm (C4.5, MLP DT) is one of the most prominent techniques used in the field of communication technology, and finally the data mining technology plays an important role in all fields. This study focused on the fields of education, health, communications and banking as data mining contributes to achieving economic development through the development of the economic field of these areas through providing accurate data for decision-making bodies in various institutions. This study also stresses that the ultimate goal of data mining is to predict human behavior, which is to a great extent the most common business application. Even though, this model can easily be formulated to meet the goal of detecting and deterring criminals. These various and important applications and many more have demonstrated that instead of having humans try to deal with hundreds of descriptive features, data mining allows automatic analysis of databases and recognizes important behavioral trends and patterns.
Keywords: Methods, Tools, Data mining, Healthcare, Big data, Business intelligence, Customer relationship management, Text mining, Web mining, Social networks

Cite this article:
Badriah Muteb Al-Otaibi. A survey study on data mining and its various important tools and applications. Acta Scientiae et Intellectus, 6(4)2020, 228-245.


  1. Ali, Hoda Abdul Rahim Hussein (2018). Using data mining technology to analyze the financial indicators of a sample of Iraqi private banks by adopting the CART algorithm. Iraqi Journal of Information Technology. Iraqi Association for Information Technology, 9(2), pp. 32-54.
  2. Ahmad, Asim Muhammad Ahmad Muhammad (2018). Using data mining techniques to discover the causes of power cuts. Master Thesis. Graduate School. University of Neelain.
  3. Zaarour, Iyad (2015). Digging into economic data and forecasts. National Institute of Administration. Lebanon Republic.
  4. Alamla, Amna Hussain (2015). Network Intrusion Classification Using Data Mining Techniques. Master Thesis. Zarqa University. Graduate School. Jordan.
  5. Lina Muhammad Al-Ghamdi (2020). Information security challenges facing cloud computing: critical appraisal study. Acta Scientiae et Intellectus, Vol.6. No.4(2020), 6, pp.82-98.
  6. Silva, Carla Sofia; Fonseca, Jose Manuel (2017). Educational Data Mining: A Literature Review. Europe and MENA Cooperation Advances in Information and Communication Technologies. 87-94.
  7. Alghobiri, Mohammed (2018). The Relationship between Secondary Education Output and University Education Input: A Data Mining Approach. Al-Azhar University-Saleh Abdullah Kamel Center for Islamic Economics, Vol. 22, No. 64.
  8. Mishra, Ved P (2018). Big Data Mining Methods in Medical Applications, Medical Big Data and Internet of Medical Things Advances, Challenges and Applications. 1-23.
  9. Mahdi, Shajan,Muhammed (2019). Diabetes Risk Level Prediction Using Data Mining Techniques. Master Thesis. Al-Isra Private University. Graduate School. Jordan.
  10. Deyu, Lulu (2014). Data Mining Approach to Analyze Mobile Telecommunications Network Quality of Services: The Case of Ethio-Telecom. Addis Ababa University.
  11. Aisha Saleh Al-Ghamdi (2020). Challenges and threats affecting information security in cloud computing. Acta Scientiae et Intellectus, 6 (2020), 6, pp.98-120.
  12. Abu Samra, Abdul Karim Ahmed (2018). Data Mining Model to Detect Android Malware Based on Permissions and Activities. Master Thesis. Islamic University of Gaza). information technology collage.
  13. Pascu, Adrianionut (2018). Data Mining Concepts and Applications in Banking Sector. Annals of the "Constantin Brâncuşi" University of Târgu Jiu, Economy Series. 159-166.
  14. Othman, Marawan Babiker Suleiman. (2018). Detecting Fraud in Banking Transaction By Using Data Mining Techniques. Ph.D. Omdurman Islamic University. Sudan.
  15. Chelhi, K. (2018). Use of Data Mining for the Assessment of the Mudaraba Performance Risk in the Light of Macroeconomic Factors. The World Journal of Economics and Business. Rafad Center for Studies and Research. 5 (3). 497-508.
  16. Zhang, Jianxi & Zhang, Changfeng & Yu, Huaizhi (2018). Research on e-commerce intelligent service based on Data Mining. MATEC Web of Conferences. Shandong Institute of Commerce and Technology, Ji'nan, Shandong, China, 1-5.