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Journal articles on the topic 'Data issues'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Singh, Gurdas, and Dr Jaiteg Singh. "Querying RDF Data: Methods and Issues." Indian Journal of Applied Research 3, no. 2 (2011): 144–45. http://dx.doi.org/10.15373/2249555x/feb2013/50.

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Kumar, S. Senthil, and Ms V. Kirthika. "Big Data Analytics Architecture and Challenges, Issues of Big Data Analytics." International Journal of Trend in Scientific Research and Development Volume-1, Issue-6 (2017): 669–73. http://dx.doi.org/10.31142/ijtsrd4673.

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3

Mrs., Sowmya A. N., Madhavi R. K. Mrs., and Rajani Byakodi Mrs. "Exploring Big Data Analytics: Issues and Tools." IJAPR Journal UGC Indexed 6, no. 2 (2018): 24–34. https://doi.org/10.5281/zenodo.14882169.

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A huge repository of terabytes of data is generated each day from modern information systems and digital technologies such as Internet of Things and cloud computing. Analysis of these massive data requires a lot of effort at multiple levels to extract knowledge for decision making. Therefore, big data analysis is a current area of research and development. The basic objective of this paper is to explore the potential impact of big data challenges, open research issues, and various tools associated with it. As a result, this article provides a platform to explore big data at numerous stages. Ad

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4

Gross, Michael. "New data issues." Current Biology 20, no. 18 (2010): R790—R791. http://dx.doi.org/10.1016/j.cub.2010.09.022.

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5

Gill, Rupali, and Jaiteg Singh. "A Review of Contemporary Data Quality Issues in Data Warehouse ETL Environment." Journal on Today's Ideas - Tomorrow's Technologies 2, no. 2 (2014): 153–60. http://dx.doi.org/10.15415/jotitt.2014.22012.

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6

Raviteja Boppana, Venkat. "Data Ethics in CRM: Privacy and Transparency Issues." International Journal of Science and Research (IJSR) 12, no. 11 (2023): 2234–41. http://dx.doi.org/10.21275/sr231115110701.

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7

Bhakare, Parimal, and Shaini Suraj. "Data Mining in Healthcare: Current Applications and Issues." International Journal of Science and Research (IJSR) 11, no. 11 (2022): 1129–31. http://dx.doi.org/10.21275/sr221118072136.

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8

Anthony, Denis. "Issues in data analysis." Nurse Researcher 22, no. 5 (2015): 6–7. http://dx.doi.org/10.7748/nr.22.5.6.s2.

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9

Alnaji, Loay A., Shorouq F. Eletter, and Ghaleb A. El Refae. "Big data: ethical issues." Global Business and Economics Review 21, no. 1 (2019): 69. http://dx.doi.org/10.1504/gber.2019.096859.

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Alnaji, Loay A., Shorouq F. Eletter, and Ghaleb A. El Refae. "Big data: ethical issues." Global Business and Economics Review 21, no. 1 (2019): 69. http://dx.doi.org/10.1504/gber.2019.10017581.

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11

Joshi, Margi, and Sharon S. Krag. "Issues in Data Management." Science and Engineering Ethics 16, no. 4 (2010): 743–48. http://dx.doi.org/10.1007/s11948-010-9223-5.

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12

Feldman, Kenneth A., William H. Yeaton, and Paul M. Wortman. "Issues in Data Synthesis." Journal of the American Statistical Association 81, no. 393 (1986): 253. http://dx.doi.org/10.2307/2288004.

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13

Wicks, A. L. "REVISITING DATA ACQUISITION ISSUES." Experimental Techniques 25, no. 6 (2001): 58–60. http://dx.doi.org/10.1111/j.1747-1567.2001.tb00048.x.

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14

YOON, HYUN SEOK. "Big Data Taxation Issues." Wonkwang University Legal Research Institute 38, no. 4 (2022): 169–88. http://dx.doi.org/10.22397/wlri.2022.38.4.169.

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Big data is the generation and analysis of valuable data in large quantities with data, and has recently been developed through convergence with artificial intelligence and the Internet of Things. Big data technology, in which a vast amount of data is collected and who can more elaborately analyze and utilize the collected data, has become an era that determines the competitiveness of a company or country. The economic value of big data is increasing day by day, and companies are generating profits by using big data not only in domestic transactions but also in international transactions. I wa

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15

Rattan, Anil K. "Data Integrity: History, Issues, and Remediation of Issues." PDA Journal of Pharmaceutical Science and Technology 72, no. 2 (2017): 105–16. http://dx.doi.org/10.5731/pdajpst.2017.007765.

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16

Seema, G. Bavachkar, Shewale Ajinkya, R. Dhende Pratik., A. Mohitkar Hrishikesh., and S. Gorwade Shubham. "Issues Regarding Big Data Confidentiality." Journal of Advancement in Software Engineering and Testing 2, no. 3 (2019): 1–4. https://doi.org/10.5281/zenodo.3571777.

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<em>This research paper is to analyze, that now a day’s data is becoming most important thing for any company, organization or any other field. Due to the growing industrialization in all sectors its getting too difficult to handle such large amount of data according to the traditional ways. The term big data means the large amount of data and the main problem regarding this big data is that, this data cannot be easily secured. In order to provide security to the big data we need to carry out a detail study to find a solution of how we can provide security to big data. Actually its just

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17

Sadhik Shaik, Mohammed. "Analyzing Data Security Issues in Cloud Platforms Like AWS." International Journal of Science and Research (IJSR) 11, no. 10 (2022): 1468–72. https://doi.org/10.21275/sr22104145515.

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18

Helms, Ronald W. "Data Quality Issues in Electronic Data Capture." Drug Information Journal 35, no. 3 (2001): 827–37. http://dx.doi.org/10.1177/009286150103500320.

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19

Strom, Brian L. "Data validity issues in using claims data." Pharmacoepidemiology and Drug Safety 10, no. 5 (2001): 389–92. http://dx.doi.org/10.1002/pds.610.

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20

S., Senthil Kumar, and Ms.V.Kirthika. "Big Data Analytics Architecture and Challenges, Issues of Big Data Analytics." International Journal of Trend in Scientific Research and Development 1, no. 6 (2017): 669–73. https://doi.org/10.31142/ijtsrd4673.

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Big Data technologies uses a new generation of technologies and architectures, designed for organizations can extract value from very large volumes of a wide variety of data by enabling high velocity capture, discovery, and or analysis. Big data is a massive amount of digital data being collected from various sources that are too large. Big data deals with challenges like complexity, security, risks to privacy. Big data is redefining as data management from extraction, transformation, cleaning and reducing. The size and variety of data lead us to think ahead and develop new and faster methods

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21

Mukul, Varshney, Garg Shivani, Jyotsna, and Kiran Rajpoot Abha. "A Study on Issues, Challenges and Application in Data Science." International Journal of Trend in Scientific Research and Development 1, no. 5 (2017): 526–33. https://doi.org/10.31142/ijtsrd2340.

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Data science, also known as data driven science, is an interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.Data science is about dealing with large quality of data for the purpose of extracting meaningful and logical results conclusions patterns. It's a newly emerging field that encompasses a number of activities, such as data mining and data analysis. It employs techniques ranging from mathematics, statistics, and information technology, computer prog

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22

Gabriel, Janet, Sheik Mohideen Abdul Latheef, and Veluswamy Jayavardhanavelu. "Issues on Management and Governance of Data Security In HEIs." International Journal of Trend in Scientific Research and Development Special Issue, Special Issue-ICAEIT2017 (2018): 243–47. http://dx.doi.org/10.31142/ijtsrd19151.

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23

Varshney, Mukul, Shivani Garg, and Jyotsna Abha Kiran Rajpoot. "A Study on Issues, Challenges and Application in Data Science." International Journal of Trend in Scientific Research and Development Volume-1, Issue-5 (2017): 526–33. http://dx.doi.org/10.31142/ijtsrd2340.

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24

P, Sabarisha Malathi, and Vanathi Dr.D. "A Study of Data Storage Security Issues in Cloud Computing." Bonfring International Journal of Software Engineering and Soft Computing 9, no. 2 (2019): 05–07. http://dx.doi.org/10.9756/bijsesc.9012.

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25

Barber, Barry. "Current issues in data protection." Medical Informatics 14, no. 3 (1989): 207–9. http://dx.doi.org/10.3109/14639238908994994.

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26

Al-Zahrani, Adel, and Mohammed Al-Hebbi. "Big Data Major Security Issues." Tehnički glasnik 16, no. 2 (2022): 197–204. http://dx.doi.org/10.31803/tg-20220124135330.

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Big data has unlocked the door to significant advances in a wide range of scientific fields, and it has emerged as a highly attractive subject both in the world of academia and in business as a result. It has also made significant contributions to innovation, productivity gains, and competitiveness enhancements. However, there are many difficulties associated with data collecting, storage, usage, analysis, privacy, and trust that must be addressed at this time. In addition, inaccurate or misleading big data may lead to an incorrect or invalid interpretation of findings, which can negatively im

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27

Richta, Tomáš. "Issues of GIS data management." Geoinformatics FCE CTU 1 (December 17, 2006): 56–63. http://dx.doi.org/10.14311/gi.1.6.

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The paper deals with current issues of spatial data modelling and management used by spatial management applications. As a case study for explaining the problem, we use comparison of two main groups of software tools covering this area GIS and CAD systems - and the posibilities of their integration. Studying its functionality, we have found two main problematic issues. The first of them is the density distribution characteristics of stored data according to described area. CAD systems are oriented towards modeling individual man-made objects and structures with relatively high level of detail,

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28

McGee, Paula. "Ethical Issues in Data Collection." Research Ethics 3, no. 2 (2007): 53. http://dx.doi.org/10.1177/174701610700300206.

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29

Tescher, Andrew G. "Spaced-based data compression issues." Journal of Electronic Imaging 8, no. 3 (1999): 301. http://dx.doi.org/10.1117/1.482678.

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30

Golab, Lukasz, and M. Tamer Özsu. "Issues in data stream management." ACM SIGMOD Record 32, no. 2 (2003): 5–14. http://dx.doi.org/10.1145/776985.776986.

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31

Fleming, Thomas R., Susan S. Ellenberg, and David L. DeMets. "Data Monitoring Committees: Current issues." Clinical Trials 15, no. 4 (2018): 321–28. http://dx.doi.org/10.1177/1740774518764855.

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Maintaining confidentiality of emerging data and ensuring the independence of Data Monitoring Committees are best practices of considerable importance to the ability of these committees to achieve their mission of safeguarding the interests of study participants and enhancing the integrity and credibility of clinical trials. Even with the wide recognition of these principles, there are circumstances where confidentiality issues remain challenging, controversial or inconsistently addressed. First, consider settings where a clinical trial’s interim data could provide the evidence regulatory auth

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32

Figler, Shauna. "Data May Reveal Real Issues." HealthcarePapers 8, no. 4 (2008): 54–56. http://dx.doi.org/10.12927/hcpap.2008.19977.

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33

Hser, Yih-Ing. "Data Sources: Problems and Issues." Journal of Drug Issues 23, no. 2 (1993): 217–28. http://dx.doi.org/10.1177/002204269302300205.

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Several nationwide data systems have been specifically designed to assemble data on prevalence of drug use. Additional information is available from other systems that are oriented to different purposes, but also collect drug-related data. National prevalence estimation efforts are variously based on one or more of these prominent data sources, which are briefly reviewed in this article. Also discussed is the utility of these existing data in terms of sampling and coverage, nature and validity of measures, methods of enumeration, and consistency of data collection over time and across systems.

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34

Molloy, Chris. "Biomanufacturers Confront Big Data Issues." Genetic Engineering & Biotechnology News 32, no. 16 (2012): 42–43. http://dx.doi.org/10.1089/gen.32.16.17.

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35

Cox, D. R., Christiana Kartsonaki, and Ruth H. Keogh. "Big data: Some statistical issues." Statistics & Probability Letters 136 (May 2018): 111–15. http://dx.doi.org/10.1016/j.spl.2018.02.015.

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36

Ali, Agha Iqbal. "Data envelopment analysis: Computational issues." Computers, Environment and Urban Systems 14, no. 2 (1990): 157–65. http://dx.doi.org/10.1016/0198-9715(90)90020-t.

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37

McMillen, Daniel P. "ISSUES IN SPATIAL DATA ANALYSIS." Journal of Regional Science 50, no. 1 (2010): 119–41. http://dx.doi.org/10.1111/j.1467-9787.2009.00656.x.

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38

Mayernik, Matthew S. "Data citation initiatives and issues." Bulletin of the American Society for Information Science and Technology 38, no. 5 (2012): 23–28. http://dx.doi.org/10.1002/bult.2012.1720380508.

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39

Nur, Zarna Elya Zakariya, and Mohd Rosli Marshima. "Physical activity prediction using fitness data: Challenges and issues." Bulletin of Electrical Engineering and Informatics 10, no. 1 (2021): 419–26. https://doi.org/10.11591/eei.v10i1.2474.

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In the new healthcare transformations, individuals are encourage to maintain healthy life based on their food diet and physical activity routine to avoid risk of serious disease. One of the recent healthcare technologies to support self health monitoring is wearable device that allow individual play active role on their own healthcare. However, there is still questions in terms of the accuracy of wearable data for recommending physical activity due to enormous fitness data generated by wearable devices. In this study, we conducted a literature review on machine learning techniques to predict s

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40

Mukherjee, Soma. "Interferometric data modelling: issues in realistic data generation." Classical and Quantum Gravity 21, no. 20 (2004): S1783—S1792. http://dx.doi.org/10.1088/0264-9381/21/20/021.

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41

Subramani, R. "Data Colonialism and Data Localization: Issues and Challenges." Shanlax International Journal of Arts, Science and Humanities 11, no. 2 (2023): 91–98. http://dx.doi.org/10.34293/sijash.v11i2.6657.

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The zeitgeist of the 21st century is warped, managed, and altogether driven by the slew of technological applications. They have usurped every activity of our life in its hold in such a way that wherever we turn, we find them interfacing, navigating, and monitoring human life. The juggernaut of trade, commerce,and marketing made the entry that has taken this world in its firm grasp and the engine of marketing is consuming data of every citizen as its fuel. This function invariably brings in vast profits to large corporations and multi-national establishments which do not feel it necessary to t

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42

Ashwini Tuppad and Shantala Devi Patil. "Data Pre-processing Issues in Medical Data Classification." Journal of Advanced Zoology 44, S6 (2023): 1079–84. http://dx.doi.org/10.17762/jaz.v44is6.2361.

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With digitalization of data and the rise of World Wide Web, access to information has been very easy and affordable. Especially the Web and the Internet have boosted research activities by facilitating access to large, publicly available medical datasets under open access scheme. These developments have resulted in explosive amounts of data being generated varying in volume, variety and velocity thus referred to as big data. Availability of such medical big data has catalyzed the research in medical predictive analytics. However, the true value of such data can be derived only after subjecting

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43

R.Manigandan. "Cloud Computing: Security Issues." Shanlax International Journal of Arts, Science and Humanities 6, S1 (2018): 115–23. https://doi.org/10.5281/zenodo.1411009.

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Cloud computing is an architecture which provides computing service through the internet on demand and pays per use access to a pool of shared resources namely networks, storage, servers, services and applications, without physically acquiring them. So it saves managing cost and time for organizations. Many industries are moving towards the cloud due to the efficiency of services provided by the pay-per-use pattern based on the resources such as processing power used, transactions carried out, bandwidth consumed, data transferred, or storage space occupied, e

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44

Sweta, Kaushik, and Rajiv Singh Dr. "A Study of Fusing Subjectivity and Distinct Issues in Data Mining." International Journal of Trend in Scientific Research and Development 2, no. 1 (2017): 1215–18. https://doi.org/10.31142/ijtsrd8228.

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The world now is overpowered with data, the computerized upheaval has made digitized data simple to catch, process, store, disperse and transmit. The measure of data appears to continue forever expanding and the advance in computerized data procurement and capacity innovation has brought about the development of immense databases. The knowledge Discovery from tremendous number of databases and gigantic volume of data is a test. Inside these masses of data lies concealed data of key significance. Sweta Kaushik | Dr. Rajiv Singh "A Study of Fusing Subjectivity and Distinct Issues in Data Mi

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45

Neylon, Cameron. "Case Study: Neglected Health Issues in Niger." Research Ideas and Outcomes 3 (October 19, 2017): e21700. https://doi.org/10.3897/rio.3.e21700.

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The project "Problemes négligés du système de santé au Niger" focusses on a core set of often-neglected issues that nevertheless have an overall negative impact on health system effectiveness in Niger. For example, poor quality maternal health services result from challenges related to the midwifery profession and from pressures from addressing the effects of illegal termination of pregnancy. Overall health system governance is undermined by weak management of human resources and health information systems as well as problems related to decentralisation of health care provision and dependence

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46

Kaushik, Sweta, and Dr Rajiv Singh. "A Study of Fusing Subjectivity and Distinct Issues in Data Mining." International Journal of Trend in Scientific Research and Development Volume-2, Issue-1 (2017): 1215–18. http://dx.doi.org/10.31142/ijtsrd8228.

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47

Giashvili, Ia, Tamar Asatiani, and Sandro Sulkhanishvili. "Issues of Using Data Mining in a Bi-System." Works of Georgian Technical University, no. 2(536) (May 16, 2025): 142–49. https://doi.org/10.36073/1512-0996-2025-2-142-149.

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The article discusses the issues of using Data Mining and BI-systems within the framework of digital transformation, in the process of setting and achieving strategic goals of business management, identifying the characteristics, methods, functionality and tasks that are solved by analysis systems. These systems are aimed at using big data efficiently. The cycle of data analysis and decision-making, which provides an effective analysis of the company's business processes, is presented. The article also defines the directions of practical use of Data Mining and BI-systems in the company's activ

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48

A., Yashwanth Reddy, Krishna A., and Rakesh Chowdary M. "DESIGN AND RECTIFICATION OF PRIVACY RELATED ISSUES TOWARDS CLOUD ENVIRONMENT." International Journal of Advanced Trends in Engineering and Technology 2, no. 2 (2017): 126–29. https://doi.org/10.5281/zenodo.1034463.

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Cloud computing changed the world around us. Nowpeople are moving their data to the cloud since data is gettingbigger and needs to be accessible from many devices. Therefore, storing the data on the cloud becomes a norm. However, thereare many issues that counter data stored in the cloud startingfrom virtual machine which is the mean to share resources incloud and ending on cloud storage itself issues. In this paper,wepresent those issues that are preventing people from adoptingthe cloud and give a survey on solutions that have been done tominimize risks of these issues. For example, the data

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49

Ali, Gholami, and Laure Erwin. "BIG DATA SECURITY AND PRIVACY ISSUES IN THE CLOUD." International Journal of Network Security & Its Applications (IJNSA) 8, no. 1 (2016): 59 to 79. https://doi.org/10.5281/zenodo.3345302.

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Many organizations demand efficient solutions to store and analyze huge amount of information. Cloud computing as an enabler provides scalable resources and significant economic benefits in the form of reduced operational costs. This paradigm raises a broad range of security and privacy issues that must be taken into consideration. Multi-tenancy, loss of control, and trust are key challenges in cloud computing environments. This paper reviews the existing technologies and a wide array of both earlier and state-ofthe-art projects on cloud security and privacy. We categorize the existing researc

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50

Namdev, Swati. "Data Mining with Big Data Its Issues and Challenges." International Journal of Computer Sciences and Engineering 7, no. 1 (2019): 862–64. http://dx.doi.org/10.26438/ijcse/v7i1.862864.

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