A data warehouse is a centralized repository that stores large volumes of structured and sometimes semi-structured data from multiple sources within an organization. It is specifically designed to support decision-making processes, particularly strategic decisions, which are long-term, organization-wide, and often complex. Strategic decision-making requires a comprehensive view of the organization, historical insights, and the ability to analyze trends, patterns, and correlations across different business functions. Data warehouses play a critical role in facilitating this by integrating and consolidating data from various operational systems, external sources, and transactional databases, enabling managers to make informed, data-driven decisions. One of the primary ways a data warehouse facilitates strategic decision-making is through its ability to provide historical and aggregated data. Unlike operational databases, which are optimized for transaction processing, a data warehouse is designed for query and analysis. This historical perspective allows managers to identify trends over time, evaluate performance, and forecast future scenarios. For instance, a retail company can use a data warehouse to analyze sales data over several years to understand seasonal trends, customer preferences, and product performance. Such insights help managers make strategic decisions about inventory management, marketing campaigns, and expansion plans. Another significant aspect is the integration of data from heterogeneous sources. Organizations often have multiple operational systems, such as customer relationship management (CRM) systems, enterprise resource planning (ERP) systems, supply chain databases, and external market research data. A data warehouse consolidates this information into a unified format, ensuring consistency and accuracy. This integrated view is crucial for strategic decisions because it allows managers to analyze the organization as a whole rather