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Answer: All of the above.
When designing the conversion logic for a data type conversion process in a data transformation project, especially one involving sensitive personal information and requiring real-time analytics performance, it is crucial to consider multiple factors. Compatibility between source and target data types ensures accurate and efficient conversion. The impact on data accuracy and integrity must be evaluated to prevent data loss or corruption, particularly with sensitive information. Performance requirements must also be considered to ensure the conversion logic supports the project's need for high query performance. Therefore, all the options listed are key considerations.
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In a data transformation project, you are tasked with implementing a data type conversion process to migrate customer data from a legacy system to Microsoft Fabric. The project has strict compliance requirements, and the data includes sensitive personal information. Additionally, the solution must support high query performance for real-time analytics. Considering these constraints, which of the following are key considerations when designing the conversion logic? (Choose all that apply)
A
Ensuring the data types of the source and target columns are compatible to prevent data loss during conversion.
B
Evaluating the impact of data type conversion on data accuracy and integrity, especially for sensitive personal information.
C
Designing the conversion logic to meet the project's performance requirements, ensuring it does not degrade query response times for real-time analytics.
D
All of the above.