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Answer: Create a partition strategy based on the patient's medical record ID, allowing for efficient querying of data within specific patient records.
Option B is the correct answer because creating a partition strategy based on the patient's medical record ID allows for efficient querying of data within specific patient records. This approach is particularly beneficial for analyzing patient records, as it enables faster query execution by reducing the amount of data scanned. Option A is incorrect because partitioning based on the patient's age alone may not be sufficient for optimizing query performance. Option C is incorrect because hash-based partitioning does not consider the data's characteristics and may not lead to optimal performance. Option D is incorrect because implementing a partition strategy is essential for optimizing query performance in patient record data scenarios.
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You are designing a data processing system for a healthcare organization that requires analyzing patient records. The data needs to be partitioned to optimize query performance and support efficient data retrieval. What partitioning strategy would you recommend, and how would you implement it in Azure Data Lake Storage Gen2?
A
Implement a partition strategy based on the patient's age, as it is the most important attribute for query performance.
B
Create a partition strategy based on the patient's medical record ID, allowing for efficient querying of data within specific patient records.
C
Use a hash-based partitioning method to distribute the data evenly across multiple partitions, regardless of the data's characteristics.
D
Do not implement any partition strategy, as the patient record data does not require optimization for query performance.
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