An As-Was dataset is specifically designed to handle historical data where attributes, like department, change over time. It preserves the state of a record (e.g., an employee’s department) as it was at any given point in the past, which is crucial for accurate historical analysis like tracking the department at the exact time of termination.

Creating a Prism report with prompted filters leverages Workday’s native reporting and dashboarding capabilities. It allows end-users to interactively select filter values (like product line and region) at runtime without needing to understand dataset creation or build their own boards, providing a controlled and user-friendly experience.

Numeric strings with formatting characters like commas (thousands separators) or currency symbols will cause a conversion error when mapped directly to a numeric Prism field. The best practice is to use a transformation in the data source mapping to remove non-numeric characters before the load, ensuring clean decimal data.

Data Blending is the core Prism capability that allows you to integrate and analyze data from disparate sources (like Workday transactional data and external data files) within a single dataset. It enables a unified view without requiring all data to reside in the Workday system initially.

While syntax validation is important, logic errors require data-level investigation. Creating a test report that shows the input values and the resulting output for specific records is the most practical, real-world method to trace through the logic of a complex formula and identify where it’s behaving unexpectedly.

Performance is often tied to data volume. Applying strategic, business-relevant filters at the dataset definition level (e.g., date range, company, region) reduces the amount of data Prism needs to process when building reports and dashboards, leading to faster load times for consumers. This is a more sustainable solution than workarounds like off-hour usage.

Integrating a Business Process Security Policy with a Prism dataset applies Workday’s existing domain and role-based security model to the data. This means users will only see data in Prism reports that they are authorized to see based on their Workday permissions (e.g., a manager sees only their department’s data), ensuring data access compliance.

Prism’s built-in analytical functions, like ‘Trend’, are designed for this exact purpose. They allow you to create dynamic time-based calculations (e.g., Period Ago, Year Ago) directly within the report definition. This is efficient, maintainable, and automatically adjusts as new data is loaded.

For data blending to be meaningful, Prism needs to know how to join or relate records from the different sources. This requires defining a common key (like Employee ID, Supplier ID) or creating matching logic using transformations. Without this, the data cannot be correctly associated, leading to inaccurate analysis.

An As-Was dataset is specifically designed to handle historical data where attributes, like department, change over time. It preserves the state of a record (e.g., an employee’s department) as it was at any given point in the past, which is crucial for accurate historical analysis like tracking the department at the exact time of termination.0