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Real-Time Big Data Processing and Analytics: Concepts, Technologies, and Domains

Year 2022, Volume: Vol:7 Issue: Issue:2, 111 - 123, 07.12.2022
https://doi.org/10.53070/bbd.1204112

Abstract

In the digital era, data is one of the most important assets since it conceals valuable information. Developers of data-intensive systems have new challenges at each level of streaming, storing, and processing large quantities of data in a variety of forms and speeds. Obtaining useful information at the proper time and place is also crucial. Since the value of information is inversely proportional to time, real-time data processing and analytics are receiving more attention. Due to the importance of real-time data processing and analytics, this study focuses on real-time data processing concepts and terminology, popular technologies used in real-time data processing and analytics, popular NoSQL storage technologies used in real-time data processing, and real-time data processing application areas. The purpose of this paper is to provide researchers of real-time analysis and developers of data-intensive systems with a comparative perspective on real-time data processing by highlighting the key characteristics of real-time data processing technologies, NoSQL storage technologies, their application domains, and selected examples from previous studies.

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Gerçek Zamanlı Büyük Veri İşleme ve Analitiği: Kavramlar, Teknolojiler ve Etki Alanları

Year 2022, Volume: Vol:7 Issue: Issue:2, 111 - 123, 07.12.2022
https://doi.org/10.53070/bbd.1204112

Abstract

Dijital çağda veriler, değerli bilgileri gizlediği için en önemli varlıklardan biridir. Veri yoğun sistemlerin geliştiricileri, çeşitli biçimlerde ve hızlarda büyük miktarda verinin akışının, depolanmasının ve işlenmesinin her düzeyinde yeni zorluklarla karşılaşmaktadır. Doğru zamanda ve yerde faydalı bilgiler edinmek de çok önemlidir. Bilginin değeri zamanla ters orantılı olduğundan, gerçek zamanlı veri işleme ve analitik daha fazla ilgi görmektedir. Gerçek zamanlı veri işleme ve analitiğin önemi nedeniyle, bu çalışmada gerçek zamanlı veri işleme kavramları ve terminolojisi, gerçek zamanlı veri işleme ve analitikte kullanılan popüler teknolojiler, gerçek zamanlı veri işlemede kullanılan popüler NoSQL depolama teknolojileri, ve gerçek zamanlı veri işleme uygulama alanları sunulmuştur. Bu makalenin amacı, gerçek zamanlı veri işleme teknolojilerinin temel özelliklerini, NoSQL depolama teknolojilerini ve bunların uygulamalarını vurgulayarak, gerçek zamanlı analiz araştırmacılarına ve veri yoğun sistem geliştiricilerine gerçek zamanlı veri işleme konusunda önceki çalışmalardan seçilmiş örnekler ile karşılaştırmalı bir bakış açısı sağlamaktır.

References

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  • Doğuç, T. B., & Aydin, A. A. (2019). CAP-based Examination of Popular NoSQL Database Technologies in Streaming Data Processing. 2019 International Artificial Intelligence and Data Processing Symposium (IDAP).
  • Dutta, K., & Jayapal, M. (2016). Big Data Analytics for Real Time Systems. https://www.researchgate.net/publication/304078196
  • Erzi, H. M., & Aydin, A. A. (2020). IoT Based Mobile Smart Home Surveillance Application. 4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 - Proceedings. https://doi.org/10.1109/ISMSIT50672.2020.9255303
  • Gavrilenko, I., Sharma, M., Litmaath, M., Tikhomirova, T., Gavrilenko, I., Sharma, M., Litmaath, M., & Tikhomirova, T. (2019). DYNAMIC APACHE SPARK CLUSTER FOR ECONOMIC MODELING.
  • Gibadullin, R. F., Baimukhametova, G. A., & Perukhin, M. Y. (2019). Service-Oriented Distributed Energy Data Management Using Big Data Technologies; Service-Oriented Distributed Energy Data Management Using Big Data Technologies. In 2019 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM).
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  • Guo, D., & Onstein, E. (2020). State-of-the-art geospatial information processing in NoSQL databases. In ISPRS International Journal of Geo-Information (Vol. 9, Issue 5). MDPI AG. https://doi.org/10.3390/ijgi9050331
  • Gürcan, F., & Berigel, M. (2018). Real-Time Processing of Big Data Streams: Lifecycle, Tools, Tasks, and Challenges; Real-Time Processing of Big Data Streams: Lifecycle, Tools, Tasks, and Challenges. In 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT).
  • Hamadou, H. ben, Bach Pedersen, T., & Thomsen, C. (2020). The Danish National Energy Data Lake: Requirements, Technical Architecture, and Tool Selection. Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020, 1523–1532. https://doi.org/10.1109/BigData50022.2020.9378368
  • Han, H., Yonggang, W., Tat-Seng, C., & Xuelong, L. (2014). Toward Scalable Systems for Big Data Analytics: A Technology Tutorial. Access, IEEE, 2, 652–687. https://doi.org/0.11 09/ACCESS.2014.2332453
  • Hegde, G. P., Tech, M., Hegde, N., & Seetha, M. (2021). SMART CITY DATA GENERATION FOR IOT APPLICATIONS USING ESSENTIAL HADOOP FRAMEWORKS. Embracing Change & Transformation-Breakthrough Innovation and Creativity, 153–160.
  • Jiang, S., Qian, X., Mei, T., & Fu, Y. (2016). Personalized Travel Sequence Recommendation on Multi-Source Big Social Media. IEEE Transactions on Big Data, 2(1), 43–56. https://doi.org/10.1109/tbdata.2016.2541160
  • Kejariwal, A., Kulkarni, S., & Ramasamy, K. (2017). Real Time Analytics: Algorithms and Systems. http://arxiv.org/abs/1708.02621
  • Khan, M. F., Azam, M., Khan, M. A., Algarni, F., Ashfaq, M., Ahmad, I., & Ullah, I. (2021). A Review of Big Data Resource Management: Using Smart Grid Systems as a Case Study. Wireless Communications and Mobile Computing, 2021. https://doi.org/10.1155/2021/3740476
  • Krishnamoorthy, R., & Udhayakumar, K. (2021). Futuristic bigdata framework with optimization techniques for wind energy resource assessment and management in smart grid. Proceedings of the 7th International Conference on Electrical Energy Systems, ICEES 2021, 507–514. https://doi.org/10.1109/ICEES51510.2021.9383710
  • Lakshman, A., & Malik, P. (2014). Cassandra - A Decentralized Structured Storage System. Dancing Times, 105(1252), 43. https://doi.org/10.1145/1773912.1773922
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Details

Primary Language English
Subjects Computer Software
Journal Section PAPERS
Authors

Uğur Kekevi 0000-0003-1839-9796

Ahmet Arif Aydın 0000-0002-4124-7275

Publication Date December 7, 2022
Submission Date November 14, 2022
Acceptance Date November 27, 2022
Published in Issue Year 2022 Volume: Vol:7 Issue: Issue:2

Cite

APA Kekevi, U., & Aydın, A. A. (2022). Real-Time Big Data Processing and Analytics: Concepts, Technologies, and Domains. Computer Science, Vol:7(Issue:2), 111-123. https://doi.org/10.53070/bbd.1204112

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