What happens if the data table to be scored is large in SAS Enterprise Miner?

What happens if the data table to be scored is large in SAS Enterprise Miner?

• A. Scoring may take longer than expected
• B. It should be scored externally using score code modules
• C. A copy of the scored data is automatically stored
• D. It requires fewer input variables

Answer: (B)

The option that indicates that scoring should be done externally using score code modules highlights an important practice in handling large datasets within SAS Enterprise Miner. When dealing with extensive data tables, the internal scoring process can become time-consuming and resource-intensive, potentially affecting performance and efficiency. By scoring externally, analysts can leverage optimized code that has better performance and speed compared to scoring within the Miner environment. This approach allows for the execution of scoring on more robust systems or in a distributed manner, which can handle larger datasets more effectively than what the Enterprise Miner interface might permit directly. Using score code modules also promotes better resource management and the ability to conduct scoring in batch processes, ensuring that large volumes of data can be processed without overloading the software's capabilities during interactive use. Therefore, this option is aligned with best practices for handling large datasets in a production environment.

The option that indicates that scoring should be done externally using score code modules highlights an important practice in handling large datasets within SAS Enterprise Miner. When dealing with extensive data tables, the internal scoring process can become time-consuming and resource-intensive, potentially affecting performance and efficiency.

By scoring externally, analysts can leverage optimized code that has better performance and speed compared to scoring within the Miner environment. This approach allows for the execution of scoring on more robust systems or in a distributed manner, which can handle larger datasets more effectively than what the Enterprise Miner interface might permit directly.

Using score code modules also promotes better resource management and the ability to conduct scoring in batch processes, ensuring that large volumes of data can be processed without overloading the software's capabilities during interactive use. Therefore, this option is aligned with best practices for handling large datasets in a production environment.