True or False: Data from operational databases is extracted and added to the data warehouse periodically.

True or False: Data from operational databases is extracted and added to the data warehouse periodically.

• A. True
• B. False
• C. Only during system upgrades
• D. It depends on the organization

Answer: (A)

Data from operational databases is indeed extracted and added to data warehouses periodically, making the assertion true. This process is essential for enabling effective data analysis and reporting. Operational databases typically handle day-to-day transactions and processes, while data warehouses serve as centralized repositories that enable historical analysis and decision-making. The periodic extraction of data allows for the integration of updated information, ensuring that the data warehouse reflects current business activities and trends. This is often achieved through an Extract, Transform, Load (ETL) process, where data is collected from various sources, transformed into a format suitable for analysis, and then loaded into the data warehouse at scheduled intervals. This regular updating allows organizations to perform advanced analytics and generate insights from their operational data. The other choices imply that the relationship between operational databases and data warehouses is less dynamic or conditional, which is not the case in standard practices where regular updates are fundamental to the functionality of a data warehouse.

Data from operational databases is indeed extracted and added to data warehouses periodically, making the assertion true. This process is essential for enabling effective data analysis and reporting. Operational databases typically handle day-to-day transactions and processes, while data warehouses serve as centralized repositories that enable historical analysis and decision-making.

The periodic extraction of data allows for the integration of updated information, ensuring that the data warehouse reflects current business activities and trends. This is often achieved through an Extract, Transform, Load (ETL) process, where data is collected from various sources, transformed into a format suitable for analysis, and then loaded into the data warehouse at scheduled intervals. This regular updating allows organizations to perform advanced analytics and generate insights from their operational data.

The other choices imply that the relationship between operational databases and data warehouses is less dynamic or conditional, which is not the case in standard practices where regular updates are fundamental to the functionality of a data warehouse.