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As a Microsoft Fabric Analytics Engineer working on a lakehouse project for a retail company, you are tasked with optimizing query performance for analytics workloads involving daily sales transactions. The company operates in multiple regions, and the data volume is expected to grow significantly over time. Considering factors such as query performance, scalability, and cost efficiency, which partitioning strategy would you implement? Choose the best option from the following: (Select one)
A
Partition the data by date, with each partition containing a single day's transactions, to facilitate efficient date range queries and manage growing data volumes effectively.
B
Partition the data by product category, with each partition containing transactions for a specific category, to enable quick analysis of sales by product type.
C
Partition the data by store location, with each partition containing transactions for a specific store, to support regional sales analysis and reporting.
D
Partition the data by customer, with each partition containing transactions for a specific customer, to personalize customer sales analysis and insights.