Final answer:
Data in a data warehouse is subject oriented, meaning that it is organized by subjects like sales or finance and is optimized for large-scale, subject-specific analysis over time rather than day-to-day transactions. It captures aggregated data that helps with strategic decision making, but it is not designed to organize complex qualitative data that captures subjective observations.
Step-by-step explanation:
In contrast to data in a database, data in a data warehouse is described as subject oriented, which means that it focuses on a specific area. This approach towards data management emphasizes the categorization and analysis of data based on topics of interest to an organization, such as sales, finance, or customer information, rather than on the ongoing operations or transactions that traditionally occupy databases used for day-to-day business processes. Data warehouses are designed to bring together large amounts of time-consuming and non-volatile data, aiding in strategic decisions rather than transaction processing. They are efficient in capturing aggregated data, which provides a consolidated view of an entity over a period, serving as a valuable resource for business intelligence and analytics.
Data in a data warehouse is typically organized, cleaned, and processed to remove inconsistencies, which makes it ideal for enterprises to query and analyse in-depth. It captures how people and systems behave, providing historical contextual insights, but it does not usually capture qualitative aspects such as what employees think or believe. Organizing such qualitative data can be notably difficult, as it involves capturing subjective observations and potentially unstructured data formats, which is not the primary focus of data warehouse architecture.