BULUTLI MA’LUMOTLAR OMBORLARIDA (DATA WAREHOUSE) SI YORDAMIDA SO‘ROVLARNI OPTIMALLASHTIRISH VA XARAJATLARNI BOSHQARISH
Keywords:
Bulutli texnologiyalar, Data Warehouse, sun’iy intellekt, SQL optimallashtirish, Machine Learning, BigQuery, Redshift, Snowflake, auto-scaling, workload management, xarajatlarni boshqarish.Abstract
Ushbu maqolada bulutli ma’lumotlar omborlari (Data Warehouse) tizimlarida
sun’iy intellekt yordamida so‘rovlarni optimallashtirish va xarajatlarni boshqarish
masalalari tahlil qilingan. Tadqiqot davomida SI texnologiyalarining SQL so‘rovlarni
tezkor bajarish, resurslardan samarali foydalanish, workload balancing hamda bulutli
xizmat xarajatlarini kamaytirishdagi ahamiyati o‘rganildi. Shuningdek, Google
BigQuery, Amazon Redshift va Snowflake platformalarida qo‘llanilayotgan
zamonaviy optimallashtirish usullari yoritib berildi. Tadqiqot natijalari SI asosidagi
texnologiyalar bulutli Data Warehouse tizimlarining samaradorligini oshirish va
xarajatlarni optimallashtirishda muhim rol o‘ynashini ko‘rsatdi.
References
1.
Ralph Kimball, Margy Ross. The Data Warehouse Toolkit: The
Definitive Guide to Dimensional Modeling. 3rd Edition. Wiley Publishing,
2013. 2.
Inmon W. H. Building the Data Warehouse. 4th Edition. Wiley
Publishing, 2005.
3.
Jiawei Han, Micheline Kamber, Jian Pei. Data Mining: Concepts
and Techniques. Morgan Kaufmann Publishers, 2011.
4.
Stuart Russell, Peter Norvig. Artificial Intelligence: A Modern
Approach. Pearson Education, 2021.
5.
Tom White. Hadoop: The Definitive Guide. O’Reilly Media, 2015.
6.
Google Cloud Documentation — bulutli ma’lumotlar omborlari va
BigQuery texnologiyalari bo‘yicha rasmiy hujjatlar.
