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Answer: Distribute the data across multiple tables based on business domains and establish clear relationships to ensure data integrity and performance.
Distributing the data across multiple tables based on business domains and establishing clear relationships (Option C) is the best practice for designing a large format dataset. This approach ensures data integrity, improves query performance, and supports scalability. Including all possible columns (Option A) can lead to unnecessary data bloat and performance issues. A single large table (Option B) simplifies the model but can severely impact performance and scalability. Prioritizing performance over data accuracy (Option D) compromises the semantic model's reliability and is not advisable for a global retail company's analytics needs.
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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with designing a large format dataset for a semantic model to support a global retail company's analytics needs. The company requires real-time insights across multiple regions with strict data compliance and cost-effectiveness. Which of the following best practices should you prioritize to ensure optimal performance, scalability, and compliance? (Choose one correct answer)
A
Include all possible columns and measures to ensure no data is missed, regardless of the dataset size.
B
Create a single large table containing all the data to simplify the model and reduce complexity.
C
Distribute the data across multiple tables based on business domains and establish clear relationships to ensure data integrity and performance.
D
Prioritize performance by reducing data accuracy and completeness to speed up query responses.