PEGACPLSA88V1 Exam Dumps : Certified Pega Lead System Architect (CPLSA) Exam 8.8

For processing weekly CSV files of customer insurance quotes and creating policy cases:

File Listener and Job Scheduler (D):

Use a file listener to read the incoming CSV file and feed the data into a data type.

Configure a job scheduler to read the records from the data type and create cases. This approach decouples the file reading and case creation processes, allowing for better control and error handling.

References:

Pega File Listener Configuration Guide

Pega Job Scheduler Documentation

To configure a process where three physicians can independently perform evaluations and ensure that only two evaluations are necessary to advance the case to the medical director, you should use the "Some" join condition in Pega.

Understanding Join Conditions in Pega:Pega provides various join conditions to handle subprocesses. The join conditions include "Any," "Some," and "All." These conditions dictate how and when the main process can proceed based on the completion of subprocesses.

Some Join Condition:The "Some" join condition allows the main process to advance once a specified number of subprocesses have been completed successfully. In this scenario, since only two out of the three physicians need to complete their evaluations for the case to move forward, the "Some" join condition is appropriate.

Configuration Steps:

Step 1: Define the subprocesses for the physicians' evaluations.

Step 2: Use the "Split For Each" shape to create multiple subprocesses.

Step 3: Configure the "Some" join condition and set the number of required completions to 2.

Step 4: Ensure that the main process waits for two evaluations before moving to the medical director review.

References:Pega Documentation on Join Conditions provides detailed steps and examples for configuring different join conditions, including the "Some" join condition.

To ensure the performance of the Pega application does not degrade over time, consider the following recommendations:

Maintain Fragmented Tables: Schedule scripts to regularly maintain and defragment tables that are frequently updated. This helps in optimizing database performance.

Purge and Archive Records: Implement purging and archiving strategies based on the company's record retention policy. This practice helps in managing data growth and ensures that the system remains performant over time.

References:

Database Maintenance

Data Archiving