A.4.3 Definition of Data Warehousing Notes

Key Characteristics of Data Warehouses

1. Subject-Oriented: Data is organized around key subjects such as customers, sales, or products, rather than specific applications.
2. Integrated: Data from different sources is cleaned, transformed, and consolidated into a consistent format.
3. Non-Volatile: Once data is entered into the warehouse, it is not updated or deleted, ensuring a stable historical record.
4. Time-Variant: Data warehouses store historical data, allowing organizations to analyze trends over time.

Situations Suitable for Data Warehousing

1. Strategic Planning
   1. Long-Term Decision Making: Organizations use data warehouses to analyze historical data and identify trends that inform strategic decisions.
   2. Example: A retail company might analyze sales data over the past five years to decide which products to promote during the holiday season.
2. Business Modeling
   1. Predictive Analysis: Data warehouses enable organizations to build models that predict future outcomes based on historical data.
   2. Example: A bank might use customer transaction data to develop credit risk models and determine loan eligibility criteria.
3. Performance Measurement
   1. Key Performance Indicators (KPIs): Data warehouses help organizations track and measure KPIs across different departments.
   2. Example: A healthcare provider might monitor patient outcomes, treatment costs, and resource utilization to improve service quality.
4. Customer Relationship Management (CRM)
   1. Personalized Marketing: By analyzing customer data, organizations can tailor marketing campaigns to specific segments.
   2. Example: An e-commerce company might use purchase history and browsing behavior to recommend products to individual customers.
5. Fraud Detection
   1. Anomaly Detection: Data warehouses store historical transaction data, making it easier to identify unusual patterns that may indicate fraud.
   2. Example: A credit card company might flag transactions that deviate from a customer's typical spending behavior.
6. Supply Chain Management
   1. Inventory Optimization: Organizations use data warehouses to analyze supply chain data and optimize inventory levels.
   2. Example: A manufacturing company might track supplier performance and delivery times to reduce stockouts and delays.