As a Microsoft Fabric Analytics Engineer working on a lakehouse project, you are tasked with optimizing the partitioning strategy for a large dataset containing customer transaction data, initially partitioned by date. The goal is to enhance query performance while considering cost efficiency and scalability. The dataset includes transactions from various customer segments (premium, regular, loyalty), across different transaction types (online, in-store, mobile), and product categories (electronics, clothing, groceries). Given these requirements, which of the following partitioning strategies would BEST meet the project's needs? Choose one option.