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Answer: Normalized data models enhance data integrity and minimize redundancy, potentially at the cost of increased query complexity and performance overhead.
Option A is correct because it accurately highlights the trade-offs of normalized data models, emphasizing improved data integrity and reduced redundancy, which are crucial for compliance and governance, despite the potential increase in query complexity. This aligns with the scenario's constraints of cost efficiency, compliance, and scalability. The other options either focus on denormalized models or the use of lookup tables without fully addressing the specific trade-offs of normalized models in the given context.
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In the context of implementing lookup tables in Delta Lake within a Microsoft Azure environment, consider a scenario where your organization is optimizing a data model for both performance and integrity. The project has key constraints including cost efficiency, compliance with data governance policies, and the need for scalable solutions. Discuss the trade-offs between normalized and denormalized data models in this scenario. Additionally, provide a code snippet demonstrating how to create a lookup table in Delta Lake and join it with a main table to retrieve additional information. Choose the option that best describes the trade-offs for normalized data models under these constraints. (Choose one)
A
Normalized data models enhance data integrity and minimize redundancy, potentially at the cost of increased query complexity and performance overhead.
B
Denormalized data models offer simplified queries and faster performance but may compromise data consistency and require more storage, impacting cost efficiency.
C
Utilizing lookup tables can optimize query performance by minimizing join operations, though it introduces additional maintenance overhead.
D
Implementing lookup tables centralizes reference data, simplifying access but may complicate the data model and increase maintenance efforts.
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