The Workday Pro Prism Analytics Exam validates your ability to design, configure, and optimize reporting solutions within the Workday ecosystem. This certification is ideal for analytics professionals, business analysts, and Workday administrators who need to demonstrate expertise in Prism Analytics and advanced reporting. This page provides a clear roadmap of exam topics, question formats, and practical preparation strategies to help you succeed in the Workday Pro Certifications program.
Use this topic map to guide your study for Workday Workday-Prism-Analytics (Workday Pro Prism Analytics Exam) within the Workday Pro Certifications path.
The exam uses multiple question types to assess both foundational knowledge and your ability to apply concepts in realistic business scenarios. Questions progress in difficulty and emphasize practical decision-making aligned with actual Workday deployments.
Effective preparation combines structured topic review with hands-on practice and timed assessments. Allocate study time proportionally to Prism Analytics, Reporting, and Workday integration topics, then validate your readiness with realistic practice questions.
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Prism Analytics configuration and dataset management typically account for the largest portion of the exam, followed by reporting design and Workday module integration. Focus your study time on building confidence in data source setup, schema design, and troubleshooting refresh failures, as these appear frequently in scenario-based questions.
In practice, you design an analytic dataset in Prism Analytics, then build reports and dashboards on top of that data, all while ensuring alignment with Workday's security and data governance policies. Understanding this workflow, from data modeling through user consumption, helps you answer questions that test cross-functional thinking rather than isolated features.
Hands-on experience with Prism Analytics dataset creation, report building, and troubleshooting is highly valuable. Prioritize labs that cover dataset refresh cycles, filter configuration, and dashboard drill-down functionality, as these skills directly map to exam scenarios and real-world job responsibilities.
Candidates often confuse data source types or miss subtle requirements in scenario questions, for example, selecting a report filter when the question requires a dataset-level calculation. Another frequent error is overlooking Workday security implications when designing reports. Careful reading and understanding the business context of each question prevents these costly mistakes.
In your final week, take a full-length timed practice test to identify remaining weak areas, then focus review sessions on those specific topics rather than re-reading all material. On exam day, manage your time by flagging difficult questions and returning to them after completing easier items, ensuring you earn all available points.
[Publishing and Visualizing Data]
What report can you run to edit and maintain your Prism import and publish schedules?
[Publishing and Visualizing Data]
You want to remove data within a Prism data source without deleting any dependent custom reports. What task can you use to do this?
[Data Prep and Transformation]
In a Prism project, you have a dataset containing customer purchase transactions, including the customer ID, purchase amount, and purchase date. You want to analyze the total purchase amount for each customer over the entire period. What transformation stage should you apply to calculate the total purchase amount for each customer?
[Security and Governance in Prism]
A Prism administrator wants to hide a field that contains employee salary information but still allow the Prism data writers to view average salaries for employees by cost center. What is the reason for hiding this field?
[Data Prep and Transformation]
A Prism data administrator combined data from multiple sources down to a final derived dataset, including current worker dat
a. There is a new requirement to append historical worker data to the dataset in a uniform layout. The historical worker data includes some, but not all, fields that align withthe current worker data. Using current worker data as the primary pipeline, how can the historical worker data points be brought in?
