Implement a star schema with a central fact table for sales transactions linked to dimension tables for time, products, customers, and stores. This approach simplifies queries and enhances performance by denormalizing dimension tables.

Adopt a snowflake schema where dimension tables are normalized to reduce data redundancy. This method involves more complex joins but can save storage space.

Use a flat schema with all sales transaction data, including product, customer, and store information, stored in a single table. This approach eliminates the need for joins but may lead to data redundancy and slower query performance.

Design a graph-based schema to model the intricate relationships between products, customers, and stores. This approach is highly flexible but may not be the most efficient for standard analytical queries.