Free C2090-632 sample questions

Correct answer: Create a single model query subject that joins the four product dimension tables and presents a denormalized view.

Creating a model query subject to consolidate the snowflake schema into a single, denormalized dimension is the best practice. This simplifies the model for report authors, improves query performance by pre-defining the joins, and makes the business view more intuitive.

Correct answer: Identify the correct join path and create a relationship shortcut with a different name to resolve the ambiguity, forcing Cognos to use the correct context.

A fan trap occurs when a one-to-many join links to another one-to-many join from the central table. The correct way to resolve this is to create query subjects that isolate the join paths. Cognos can generate a stitched query to correctly bring the data together. Often, creating a shortcut to the relationship or creating separate query subjects for different contexts is the standard solution.

Correct answers: Create a separate namespace for each data source to isolate the physical metadata.; Create a third, separate namespace for the business/presentation view that references objects from the source namespaces.

Isolating metadata from each data source into its own namespace is a fundamental best practice. It prevents naming conflicts, clarifies data lineage, and simplifies maintenance.

A layered modeling approach involves creating a separate namespace for the business view. This abstraction layer uses shortcuts to the physical namespaces, providing a stable and user-friendly interface for report authors that is insulated from changes in the underlying sources.

Correct answer: Create a security filter on the `DoctorFacilityAccess` query subject for the `DoctorGroup` with the expression: `[PhysicalLayer].[DoctorFacilityAccess].[DoctorID] = #$loggedInDoctorID#`.

This is the correct approach. By applying the filter to the security table `DoctorFacilityAccess`, you restrict its contents to only the facilities associated with the logged-in doctor. Because this table is joined to the fact table (likely through a facility dimension), the filter propagates through the model, correctly securing the `PatientEncounters` data. Applying the filter to the security mapping table itself is the most efficient and maintainable design. graph TD subgraph SecurityContext User[User Login] --> SessionParam["#loggedInDoctorID#"]; end subgraph Model subgraph SecurityFilter [Filter applied to DoctorGroup] SessionParam -->|Filters| DoctorFacilityAccess[DoctorFacilityAccess Table]; end DoctorFacilityAccess -->|Joins to| FacilityDim[Facility Dimension]; FacilityDim -->|Joins to| PatientEncounters[PatientEncounters Fact]; end PatientEncounters --> Report[Secured Report Data];

Correct answer: True

This is true. Framework Manager provides this behavior as a convenience for modelers. When it detects that a numeric data item is being reclassified as a Fact, it assumes the most common aggregation function, Sum, should be applied. The modeler can then change it to another function like Average or Count if needed.

Correct answer: Determinants

Determinants are used to describe the levels of granularity within a dimension. By defining a determinant for the Month level (uniquely identified by Month_Key) and another for the Day level (uniquely identified by Day_Key), you inform the Cognos query engine about the data's structure. When a query involves the Month-level forecast fact, Cognos will aggregate correctly at the month level and will not incorrectly multiply the forecast values across all days.

Correct answer: There is no valid relationship path defined between the 'Customer' and 'Sales' query subjects in the model.

The Cognos query engine generates a cross-product when it cannot find a valid join path between the tables included in a query. This is most commonly caused by a missing or incorrectly defined relationship between the relevant query subjects. Without a defined join on a common key (e.g., Customer_ID), the engine has no choice but to join every row from the first table to every row in the second. graph LR subgraph "Problem State" Customer[Customer QS] -- "No Relationship" -- Sales[Sales QS] Customer --> CrossJoin((Cross Product)) Sales --> CrossJoin end subgraph "Correct State" Customer_Correct[Customer QS] -- "1..n on Customer_ID" --- Sales_Correct[Sales QS] Customer_Correct --> InnerJoin((Inner Join)) Sales_Correct --> InnerJoin end

Correct answers: Parameter Maps; Session Parameters

Parameter maps are key-value pairs stored within the model. They are ideal for managing static lists of values, such as translations for report titles or mapping codes to descriptive names. The session parameter for language can be used as the key to look up the correct title.

Session parameters hold values that are specific to a user's session, such as user name, account information, or preferred language. They are perfect for driving dynamic behavior like security filters, where the user's region can be passed from the authentication source and used in a macro.

Correct answer: Create one model query subject for 'Ports', then create two shortcuts (aliases) to it named 'Origin Port' and 'Destination Port', and join each shortcut to the appropriate key in the fact table.

This is the standard and most efficient method for handling role-playing dimensions. A single query subject for 'Ports' is maintained. Shortcuts (which act as aliases) are then created for each 'role' (Origin and Destination). This allows for unambiguous join paths to the fact table while maintaining a single point of definition for the port dimension, simplifying maintenance.

Correct answer: Ability to reference query items from multiple query subjects.

Stand-alone calculations can reference query items from any query subject that has a relationship path to the others used in the expression. This allows for the creation of complex business logic (like profit margin, which needs revenue and cost from different subjects) that spans multiple tables. Embedded calculations are limited to items within the same query subject.