DEVELOPMENT OF A HYBRID METHOD FOR DATA WAREHOUSE CONSTRUCTION-Reference-Cited by-同舟云学术

DEVELOPMENT OF A HYBRID METHOD FOR DATA WAREHOUSE CONSTRUCTION

Published:2024-06 Issue:1 Volume:6 Page:67-80
ISSN:2707-2371
Container-title:Computer systems and network
language:
Short-container-title:CSN

Author:

Koval O.,Harasymchuk O.

Abstract

The examined approach to building an adaptive and convenient data warehouse goes beyond simple data storage focusing on processing data for various types of reports and analytics. It allows for more efficient use of data resources and ensures a flexible response to changing business needs. This hybrid method combines several techniques and technologies to provide the best possible performance and scalability. The article discusses the main challenges and benefits of this approach and presents a detailed analysis of the architecture and components of the proposed data warehouse system. The results show significant improvements in data processing speed and accuracy compared to traditional methods. Key words: data warehouse hybrid method data processing scalability.

Publisher

Lviv Polytechnic National University

Reference15 articles.

1. Minukhin, S., Fedko, V., & Gnusov, Y. Enhancing the performance of distributed big data processing systems using Hadoop and PolyBase. Eastern-European Journal of Enterprise Technologies, 4(2–94), (2018). pp. 16–28. •DOI:10.15587/1729-4061.2018.139630.

2. Praveen Kumar, Dr. Kavita The Study On Data Warehousing Different Concepts Vol. 21 No. 16 (2019), pp.3103-3109/. Available at: http://gujaratresearchsociety.in/index.php/JGRS/article/view/3497 (Accessed: 10 March 2024).

3. W. H. Inmon. Building the Data Warehouse,3rd Edition (3rd. ed.). John Wiley & Sons, Inc., USA. 2002. Avaible at: https://fit.hcmute.edu.vn/Resources/Docs/SubDomain/fit/ThayTuan/DataWH/ Bulding%20the%20Data%20Warehouse%204%20Edition.pdf (Accessed: 10 March 2024)

4. Bhatia, P. (2019) Data Mining and Data Warehousing: Principles and Practical Techniques. Cambridge University Press, Cambridge. •DOI:10.1017/9781108635592.

5. Padmaja Potinen/ Oracle Database Data Warehousing Guide, 21c. Copyright © 2001, 2022, Oracle and/or its affiliates. Available at https://docs.oracle.com/en/database/oracle/oracle-database/21/dwhsg/preface.html#GUID-9CDC42C7-5BB2-4433-9F3E-ADE92929A0EA (Accessed: 10 March 2024)