MODERN DATA WAREHOUSING AND DATA MINING ARCHITECTURES FOR ADVANCED ANALYTICS APPLICATIONS

The blistering development of data produced by the enterprise systems, clouds, social media, and Internet of Things (IoT) devices has triggered the rise of a high demand among scalable and smart data management and analytics solutions. The conventional data warehousing models which are mostly structured and batch oriented are progressively falling short of processing the volume, velocity and variety of current data. To counter these issues, contemporary data warehousing designs alongside data mining algorithms have become a vital basis to enhanced analytics and information-based decision-making. The chapter is a thorough analysis of current data warehousing and data mining architecture, its development, blending and use in advanced analytics environments. An insightful survey of the existing literature helps to identify the major trends in the cloud-based data warehouse, data lakes, and lakehouse architectures, along with the increase in the importance of data mining and machine learning methods in data analysis. Riding on such understanding, the chapter suggests a unified architectural design that incorporates the use of modern data warehousing infrastructures with built data mining and analytics functionality to enable scalable, flexible, and efficient data analysis. In order to show the relevance of the proposed framework in practical context, a case study of retail analytics is provided which explains the use of cloud-based data warehousing and data mining methods to achieve customer segmentation, demand prediction, and business intelligence. The outcomes of the case study represent high rates of growth in analytical performance, decision-making rate, and the operational efficiency. Another important point that the chapter addresses is the problems associated with data quality, security, governance, and skills requirements, and the future research directions, including AI-driven data warehouses, real-time analytics, and autonomous data management systems