The Role of Machine Learning in Data Warehousing: Enhancing Data Integration and Query Optimization
Keywords:
machine learning, data warehousingAbstract
ML might change data warehousing's dynamic process. This research analyzes how ML enhances data warehouse queries and integration. Big data warehouses with different data limit efficiency, scalability, and retrieval. Complex data sets make data integration and query optimization fail. The procedures may benefit from ML.
Machine learning can automate and improve data integration by finding patterns and insights in vast datasets. Integration of heterogeneous data warehouse sources is improved by ML schema matching, data purification, and transformation. Supervised and unsupervised ML may reduce mapping and transformation errors. ML anomaly detection may improve data warehouse quality.
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