INTELLIGENT DATA ANALYSIS ON AN ANALYTICAL PLATFORM
Dauren Darkenbayev
dauren.kadyrovich@gmail.comAl-Farabi Kazakh National University (Kazakhstan)
https://orcid.org/0000-0002-6491-8043
Arshyn Altybay
Al-Farabi Kazakh National University (Kazakhstan)
https://orcid.org/0000-0003-4939-8876
Zhaidargul Darkenbayeva
Kazakh Ablai Khan University of International Relations and World Languages (Kazakhstan)
https://orcid.org/0000-0003-3756-0581
Nurbapa Mekebayev
Kazakh National Women’s Teacher Training University (Kazakhstan)
https://orcid.org/0000-0002-9117-4369
Abstract
The article discusses methods for processing unstructured data using an analytical platform. The authors analyze existing methods and technologies used to implement data processing and propose new approaches to solving this problem. The possibilities of using analytical platforms to solve the problem of processing source data are considered. The purpose of the article is to explore the possibilities of data import, partial preprocessing, missing data recovery, anomaly removal, spectral processing and noise removal. The authors explored how analytics platforms can function without a data warehouse, obtaining information from any other sources, but the most optimal way is to use them together, and how big data and unstructured data can be processed using an analytics platform. The authors solved a specific problem related to processing problems and proposed ways to solve them using an analytical platform. Particular attention is paid to a complete set of mechanisms that allows you to obtain information from any data source, carry out the entire processing cycle and display the results. Overall, the paper represents an important contribution to the development of raw data processing technologies. The authors plan to continue research in the field of processing big unstructured data.
Keywords:
raw data, processing, analytical platform, technology, analysisReferences
Abdiakhmetova Z. M.: Wavelet data processing in the problems of allocation in recovery well logging. Journal of Theoretical and Applied Information Technology 95(5), 2017, 1041–1047.
Google Scholar
Altybay A. et al: Numerical Simulation and Parallel Computing of the Acoustic Wave Equation. AIP Conference Proceedings 3085(1), 2024, 020006.
DOI: https://doi.org/10.1063/5.0194676
Google Scholar
Balakayeva G. et al: Development of an application for the thermal processing of oil slime in the industrial oil and gas sector. Informatics, Control, Measurement in Economy and Environmental Protection 13(2), 2023, 20–26.
DOI: https://doi.org/10.35784/iapgos.3463
Google Scholar
Balakayeva G. et al: Digitalization of enterprise with ensuring stability and reliability. Informatics, Control, Measurement in Economy and Environmental Protection 13(1), 2023, 54–57 [http://doi.org/10.35784/iapgos.3295].
DOI: https://doi.org/10.35784/iapgos.3295
Google Scholar
Balakayeva G., Darkenbayev D.: The solution to the problem of processing Big Data using the example of assessing the solvency of borrowers. Journal of Theoretical and Applied Information Technology 98(13), 2020, 2659–2670.
Google Scholar
Balakayeva G. T. et al: Using NoSQL for processing unstructured Big Data. News of the NAS of the Republic of Kazakhstan 6(438), 2019, 12–21.
DOI: https://doi.org/10.32014/2019.2518-170X.151
Google Scholar
Big Data Big Opportunity [http://www.oracle.com] (28.01.2012).
Google Scholar
Darkenbayev D. K.: Numerical solution of the regression model for analysis and processing of Big Data. Vestnik KazNRTU 6(130), 2018, 132–139.
Google Scholar
Franks B.: The Taming of Big Data: How to Extract Knowledge from Arrays of Information Using Deep Analytics. Mann, Ivanov and Ferber, 2014, 180.
Google Scholar
Highlights: Unique Features of Statistica Data Miner [http://www.statsoft.com] (01.02.2014).
Google Scholar
Lubanovic B.: Introducing Python: Modern Computing in Simple Packages 2nd Edition. O'Reilly Media, 2019.
Google Scholar
Rastorguev V.: DataMining technology for data analysis in credit scoring methods. Banking Technologies (11), 2003, 14–18.
Google Scholar
Rimmer J.: Contemporary changes in credit scoring. Credit Control 26 (4), 2005, 56–60.
Google Scholar
Saar-Tsechansky M., Provost F.: Active sampling for class probability estimation and ranking. Machine Learning 54(2), 2004, 153–178.
DOI: https://doi.org/10.1023/B:MACH.0000011806.12374.c3
Google Scholar
Semenov Yu. A.: Large amounts of data (big data) [http://book.itep.ru] (21.04.2013).
Google Scholar
Usachev S.: Credit scoring: desktop or enterprise solutions. Banks and technologies (4), 2008, 50–54.
Google Scholar
[http: //www.basegroup.ru].
Google Scholar
[http://www.nosql-database.org].
Google Scholar
[https://basegroup.ru/deductor/components/studio].
Google Scholar
Authors
Dauren Darkenbayevdauren.kadyrovich@gmail.com
Al-Farabi Kazakh National University Kazakhstan
https://orcid.org/0000-0002-6491-8043
Authors
Arshyn AltybayAl-Farabi Kazakh National University Kazakhstan
https://orcid.org/0000-0003-4939-8876
Authors
Zhaidargul DarkenbayevaKazakh Ablai Khan University of International Relations and World Languages Kazakhstan
https://orcid.org/0000-0003-3756-0581
Authors
Nurbapa MekebayevKazakh National Women’s Teacher Training University Kazakhstan
https://orcid.org/0000-0002-9117-4369
Statistics
Abstract views: 338PDF downloads: 136
Most read articles by the same author(s)
- Nataliia Geseleva, Ganna Proniuk, Olexander Romanyuk, Olga Akimova, Tetiana Troianovska-Korobeynikova, Liudmyla Savytska, Saule Rakhmetullina, Nurbapa Mekebayev, MANAGEMENT OF THE WORKPLACES BY THE FACILITIES OF OPERATIONS RESEARCH , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 12 No. 3 (2022)
- Gulnar Balakayeva, Paul Ezhilchelvan, Yerlan Makashev, Christofer Phillips, Dauren Darkenbayev, Kalamkas Nurlybayeva, DIGITALIZATION OF ENTERPRISE WITH ENSURING STABILITY AND RELIABILITY , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 13 No. 1 (2023)
- Gulnar Balakayeva, Gaukhar Kalmenova, Dauren Darkenbayev, Christofer Phillips, DEVELOPMENT OF AN APPLICATION FOR THE THERMAL PROCESSING OF OIL SLIME IN THE INDUSTRIAL OIL AND GAS SECTOR , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 13 No. 2 (2023)
- Gulnar Balakayeva, Dauren Darkenbayev, Mukhit Zhanuzakov, DEVELOPMENT OF A SOFTWARE SYSTEM FOR PREDICTING EMPLOYEE RATINGS , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 13 No. 3 (2023)
