Big Data Analytic System: Tool for Real-Time Information Verification

Onyekwelu; Chidinma A; Prof. Anigbogu; S. O.

doi:10.56201/ijefm.v9.no9.2024.pg268.279

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Big Data Analytic System: Tool for Real-Time Information Verification

Onyekwelu, Chidinma A and Prof. Anigbogu, S. O.

Abstract

Big data is related to the extraction of large and complex data into meaningful data which can not be extracted or analyzed by traditional methods. Storing and retrieving vast amount of structured as well as unstructured data at desirable time is undergoing challenges in the big data and real time system. Big data analytics serves as a powerful catalyst for business growth and performance optimization. By transforming raw data into actionable insights, it empowers businesses to make informed decisions-makers and enhance customer experiences. The process of big data analysis involves identifying trends and patterns within data sets, thereby facilitating the extraction of meaningful conclusions. Information verification provides accurate, clean, and complete information that has been eliminated data errors and ensure that the data is not corrupted. Big data anlytic system was discussed in this paper as a tool for real-time information verification and as means of overcoming the limitations in handling and processing large amounts of data using conventional storage techniques, in order to provide accurate and reliable information effective for jurdiscious management of organization and decision-making. This paper was able to discuss conceptual/theoritical framwork, big data analytic processes, types, clasification, methods and its importances of big data analytic system.

Keywords

AnalyticAnalytic SystemDataBig DataBig data analyticInformation

References

Abhay, B. and Dhanya, J. (2020). Big Data: Challenges, Opportunities, and Realities. https://arxiv.org/ftp/arxiv/papers/1705/1705.04928.pdf Adam Purslow (2023). Real-Time Verification. CEO, TheLoyaltyCo Adeyemo, A. B. and Ojo, A. K. (2019). Classification of social blogs comments using textmining. International Journal of Computer Science Issues, 11(6), 54-58. Aspena, O. (2021). the Importance of Data Verification and Validation for Accurate Insights, Retrieved from: https://aspenasolutions.com/the-importance-of-data-verification-and- validation Avinash, B. Arpana, K. (2020). RaajHans: A Data Mining Tool Using Soft Computing Techniques. International Journal of Computer Applications (IJCA).7(11). 223 - 228 Bello, V. (2021). Computerized Crime Tracking System, International Journal of Innovative Research in Science, Engineering and Technology (IJIRSET), ..7, no. 6, pp. 362 – 368, Biem, M., Linda, N. and Fren, B. (2020). IBM infosphere streams for scalable, real-time, intelligent transportation services. Proceedings of the 2020 ACM SIGMOD International Conference on Management of data.ACM, 2020. Boyd, D., & Crawford, K., (2017). Six provocations for big data. In: A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society. El Houari, M., Rhanoui, M. & El Asri, B., (2022). From Big Data to Big Knowledge: The art of making Big Data alive. International Conference on Cloud Technologies and Applications. Fatima, F., Islam, Z. W., Zafar, F., & Ayesah, S. (2020). Impact and usage of internet in education in Pakistan. European Journal of Scientific Research, 47(2), 256-264. Hilbert, B. & Lopez, O. (2021). The world technological capacity to store, communicate, and compute information (PDF). Science. 332 (6025): 60–5. Bibcode:2011Sci...332...60H. doi:10.1126/science.1200970. PMID 21310967 Hu, J. & Meng, K. (2020). Automatic data extraction from data-rich web pages.Applied Optics. 30 (29): 4211–7. Bibcode: 2020 ApOpt..30.4211Z. doi:10.1364/AO.30.004211.PMID Machala, P., Sondos, U. and Blessing, M. (2023). Criminal Face Detection System.Using the Fisherface algorithm and the Local Binary Patterns Histogram (LBPH) classifier. 7th International Annual Engineering Seminar (Yogyakarta) Mannino, M. & Effelsberg, W. (2020). Matching Techniques in Global Schema Design”, In Proceedings of the First International Conference on Data Engineering (ICDE 2020), Los Angeles, California, 418-425, 2020 Muhammad, M., Nur, M., Ghazali, O. and Siti, H. (2021). Age Group Classification using Con.utional Neural Network (CNN). Journal of Physics: Conference Series 2084 (2021)012028 doi:10.1088/1742-6596/2084/1/012028. Nwankwo, P. (2023). Predictive Model for Detecting Underage Voters using Deep Learning and Blockchain Technology. International Conference on Advancement in Electrical and Electronic Engineering (Gazipur: IEEE) pp 24–7 Segun, N., Benard, F. & Peter, J. (2022). Biometric Specifications for Personal Identity Verification (PDF): NIST SP 800–76–2. doi:10.6028/nist.sp.800-76-2. Urquhart, C., Lehmann, H., & Myers, M. D. (2019). Putting the ‘Theory’ Back into Grounded Theory: Guidelines for Grounded Theory Studies in Information Systems.Information Systems Journal, 20(4), 357-381 Waller, M. & Fawcett, S., (2020). Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management. Journal of Business Logistics, 34(2). 77-84

Big Data Analytic System: Tool for Real-Time Information Verification

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