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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with integrating data from multiple sources into a single data warehouse for a financial services company. One of the sources is a financial transaction system that uses a different data format and schema than the other sources. The company requires real-time analytics on all data, including financial transactions, to make timely business decisions. Considering the need for data consistency, real-time access, and minimal maintenance overhead, which of the following approaches would you recommend for integrating the financial transaction data? (Choose one option.)
A
Transform the financial transaction data to match the data format and schema of the other sources before loading it into the data warehouse, ensuring data consistency and enabling real-time analytics.
B
Create a separate schema within the data warehouse to accommodate the unique data format and schema of the financial transaction system, allowing for direct querying but increasing maintenance complexity.
C
Exclude the financial transaction data from the data warehouse due to the differences in data format and schema, focusing on the remaining data for analytics.
D
Use a data virtualization approach to access the financial transaction data without physically loading it into the data warehouse, reducing storage costs but potentially impacting query performance.