Final answer:
A conformed dimension is a dimensional element that ensures consistency and accuracy in data analysis and reporting across different data sources in a data warehouse. It offers advantages such as consistency, flexibility, and reduced complexity. An example of a conformed dimension is 'Date' which can be used across various data sources in a data warehouse.
Step-by-step explanation:
A conformed dimension is a dimensional element that has the same definition and attributes across different data sources in a data warehouse. It helps ensure consistency and accuracy in data analysis and reporting.
The advantages of using conformed dimensions are:
- Consistency: Conformed dimensions allow for consistent analysis and reporting by providing a uniform definition across different data sources.
- Flexibility: The use of conformed dimensions enables the integration of data from multiple sources, allowing for more comprehensive analysis and reporting.
- Reduced complexity: Conformed dimensions simplify the data warehouse design by eliminating the need to replicate dimension tables for each data source.
For example, a conformed dimension like 'Date' can be used across different data sources in a data warehouse, such as sales, inventory, and customer data. This allows for consistent analysis and reporting regardless of the source of the data.