DATA WAREHOUSING AND ANALYTICAL DATABASES IN CONTEMPORARY DECISION SUPPORT
Keywords:
data warehouse, analytical databases, decision support, business intelligence, data integration, OLAP, Amazon Redshift, Snowflake, Oracle.Abstract
This article examines how data warehousing and analytical databases contribute to modern decision support systems. It analyzes the integration and management of large-scale data from multiple sources, enabling organizations to extract actionable insights. The study explores the advantages, applications, and challenges of data warehouses, highlighting the importance of structured data management for informed strategic and operational decisions. Real-world database systems such as Oracle, Amazon Redshift, and Snowflake are discussed as examples of practical implementations in contemporary organizations.
References
1. Inmon, W. H. (2014). Building the Data Warehouse. Wiley.
2. Kimball, R., & Ross, M. (2013). The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. Wiley.
3. Oracle Corporation. (2021). Oracle Data Warehousing Solutions. Retrieved from https://www.oracle.com/data-warehousing/
4. Amazon Web Services. (2022). Amazon Redshift Documentation. Retrieved from https://docs.aws.amazon.com/redshift/
5. Snowflake Inc. (2022). Snowflake Data Cloud Overview. Retrieved from https://www.snowflake.com/
6.



