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Answer: All of the above.
When selecting a database template optimized for analytical workloads, it is important to consider several factors. The data volume and the complexity of the analytical queries (Option A) will determine the required processing power and storage capacity. The performance requirements and the expected concurrency levels (Option B) will impact the system's responsiveness and ability to handle multiple users. The compatibility of the database template with existing ETL processes and data sources (Option C) ensures seamless integration and reduces the need for additional modifications. Therefore, all of these factors should be considered when selecting a database template, making Option D the correct answer.
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As a Microsoft Azure Data Engineer Associate, you are responsible for recommending Azure Synapse Analytics database templates for a new project. What factors should you consider when selecting a database template that is optimized for analytical workloads?
A
The data volume and the complexity of the analytical queries.
B
The performance requirements and the expected concurrency levels.
C
The compatibility of the database template with the existing ETL processes and data sources.
D
All of the above.
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