Pegasystems PEGACPSA23V1 - Certified Pega System Architect

pyWorkPage is a central concept in Pega, serving as the primary page that contains all the data associated with a particular case as it is being created and processed:

D. pyWorkPage contains all the case data generated while creating and processing a case. This page acts as the primary clipboard page for a case, holding all data entered by the user, data generated by the system, and data that might be populated from other sources or data pages throughout the case lifecycle. It essentially serves as the working memory for the case instance.

To ensure that the date of birth submitted for first-grade students meets the requirement of being at least five years before September 1 of the current year, a combination of validation methods is necessary for comprehensive and effective validation.

A. When rule: Can be used to determine if the provided date of birth satisfies the age condition relative to September 1 of the current year, serving as a condition in process flows or UI elements.

D. Validation rule: Enables the definition of broader validation criteria that can encompass complex logic, including checking the student's age based on their date of birth in relation to a specific cutoff date.

E. Edit validate rule: Provides a mechanism for implementing pattern-based validations or more intricate checks, including verifying that a date of birth makes a student eligible for first grade based on age.

Calendar control (B) facilitates user input but does not enforce the specific age requirement on its own. Using the Date data type (C) ensures the field accepts dates, but without additional validation logic, it doesn't guarantee compliance with the age requirement.

To automatically calculate the total hours worked, including vacation and sick time, on a timesheet entry form:

B. Use declarative processing. When the value of any work, vacation, or sick time changes, the total hours change. Declarative processing in Pega is ideal for this situation as it allows the total hours to automatically update whenever the constituent values change. This approach ensures real-time accuracy and reduces the need for manual recalculations or procedural coding.

The appropriate scope for a data page that lists products purchased by a customer viewed in an online portal is "Requestor". This scope ensures that the data page is unique to each user session and is accessible across multiple requests within that session. The "Requestor" scope is suitable because it persists for the duration of the user's interaction with the application, across multiple threads or cases, making it ideal for situations where a user might be working on multiple support requests during a single login session.

Similar to the previous validation question, using a single Validate rule that encompasses both conditions—minimum monthly income of GBP 2000 and a maximum credit card debt of GBP 20000—is the most straightforward and efficient approach. This ensures that all financial criteria are assessed together, maintaining consistency and simplicity in the validation process, and preventing the application from moving forward if either financial criterion is not met.

In scenarios involving a large dataset, such as a database of over 10,000 book titles, the most efficient way to allow users to find and select an item is by using an autocomplete control. This approach enhances user experience by filtering options based on user input, making it easier to navigate through large lists of data.

Why not a drop-down? A drop-down control (Options A and B) would not be practical for such a large number of items because it would require loading all items at once, which can lead to performance issues and a poor user experience.

Why an autocomplete control? The autocomplete control (Option C) is designed for scenarios like this. It allows the user to begin typing the name of a book, and the control suggests matching titles based on the input, narrowing down the options dynamically. This approach is much more user-friendly and efficient for large datasets.

Why sourced from a data page? Sourcing the autocomplete control from a data page (Option C) is the best practice because it allows for the efficient loading and caching of data. Data pages can be configured to refresh at appropriate intervals or under specific conditions, ensuring that the data is up-to-date. Furthermore, using a data page abstracts the data source from the control, making the application easier to maintain and update.

This setup ensures a smooth and efficient user experience, allowing for quick and easy selection from a vast database of book titles

Given the updated business requirement allowing the parent Accident Claim case to continue independently of the status of the child cases:

D. Configure the step so that users can continue with the parent case process regardless of child case status. The Wait step previously used to pause the parent case should be removed or configured to not halt the parent case processing, thereby permitting the parent case to proceed without dependency on the child cases' progress or resolution. This change reflects the new requirement for the parent case to operate independently from the Vehicle Damage (VD-001) and Body Injury (BI-001) child cases.

In Pega, when configuring data pages to source UI controls such as drop-down lists, it's crucial to select the configuration that optimally uses memory and efficiently serves the data to the users. For this scenario, the correct answer is Option F: List, ACME-Products-Data-Color, ReadOnly, Node.

List vs. Page: Choosing 'List' is appropriate because the requirement is to populate a drop-down list with multiple entries (colors in this case). 'Page' would be used for single record data, which is not the case here.

Object Type: 'ACME-Products-Data-Color' is chosen because the data represents a list of color options provided by the manufacturer, which is typically static reference data, fitting the 'Data' class layer rather than the 'Work' layer which is used for case management or the 'Work-ColorFeedback' which would be used for storing feedback or interactions specific to colors.

Edit Mode: 'ReadOnly' is the correct mode since users are selecting a color from a pre-defined list and are not expected to edit these values directly.

Scope: 'Node' is selected to minimize memory usage. By setting the scope to 'Node', the data page is loaded once per node (server instance) and shared across all requestors (users) on that node, which is memory efficient for data that doesn't change often and is applicable across all users, such as a list of colors.

This configuration ensures that the data page is loaded efficiently in a read-only list format at the node level, reducing the overall memory footprint while making the color selections available across the application.

To create a visualization for managers to track the number and status of Customer Support Request cases:

D. Create a new Insight on the Explore data landing page. Insights in Pega allow you to create visual representations of data, which can include reports and dashboards. Managers can use these insights to track case metrics over specified time frames, such as the last 30 days.

For a user view that includes a list of four urgency options selectable by radio buttons, the goal is to present a single choice among predefined options in a user-friendly manner.

C. Configure a picklist with radio buttons for the urgency options: This approach directly meets the requirement by allowing users to select one urgency level from the provided options using radio buttons. A picklist configured with radio buttons effectively presents discrete choices in a clear format, ensuring that only one urgency option can be selected at any time, which aligns with the functionality described.

Configuring a field group (A) is generally used for grouping related fields but does not inherently provide the singular selection mechanism of radio buttons.