Question 1 of 30
A retail company is analyzing its sales data to understand customer purchasing behavior. They have a dataset that includes customer IDs, product IDs, purchase dates, and quantities sold. The company wants to create a data model that allows them to analyze sales trends over time and by product category. Which of the following approaches would best facilitate this analysis while ensuring that the data model remains efficient and scalable?
Create a star schema with a central fact table for sales transactions and dimension tables for customers, products, and time.
Use a snowflake schema that normalizes the product dimension into multiple related tables to reduce redundancy.
Implement a flat file structure that combines all data into a single table to simplify queries.
Design a data model with multiple fact tables for each product category to isolate sales data.

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