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Answer: Implement a comprehensive solution combining data pipelines for bulk data transfer, dataflows for structured data processing, and notebooks for unstructured data transformation, ensuring efficiency and minimal downtime.
The best approach is to combine data pipelines, dataflows, and notebooks. Data pipelines efficiently handle the large volume of data transfer, dataflows are optimized for processing structured data, and notebooks provide the flexibility needed for unstructured data transformation. This integrated approach ensures the migration is efficient, scalable, and minimizes downtime, meeting all specified requirements.
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As a Microsoft Fabric Analytics Engineer, you are planning a migration of a large dataset from a Fabric data source to a lakehouse. The dataset includes both structured and unstructured data, and the migration must be completed with minimal downtime while ensuring cost-effectiveness and scalability. Considering these requirements, which of the following approaches would you choose? (Choose the best option.)
A
Utilize a single data pipeline with a batch processing approach to migrate all data types simultaneously, prioritizing simplicity over processing efficiency.
B
Separate the migration process by using dataflows for structured data and notebooks for unstructured data, without integrating these processes to streamline the migration.
C
Employ Fast Copy for the entire dataset to expedite the migration process, disregarding the need for data transformation or processing during migration.
D
Implement a comprehensive solution combining data pipelines for bulk data transfer, dataflows for structured data processing, and notebooks for unstructured data transformation, ensuring efficiency and minimal downtime.