C_HAMOD_2404 SAP Certified Associate - Data Engineer - SAP HANA Questions and Answers

The block must start with a node that defines a table as a data source (C):Parallelization blocks are designed to work with table-based nodes as starting points for splitting workloads.

Only one block can be defined across a stack of calculation views (D):This restriction ensures consistency and avoids conflicts during parallel execution.

Areferential joinis chosen to ignore unnecessary data sources, as it assumes that corresponding records exist in the target table for every record in the source table. This join type avoids querying the target table when the data is not required, improving performance while maintaining logical integrity.

Implementing data replication involves these steps:

B. Create a remote subscription: Captures changes from the source system.

C. Create a target table: Stores replicated data in the target system.

E. Create a virtual table: Establishes access to the remote data source.

Enabling the linked database feature (A) and defining a flowgraph (D) are useful for related tasks but are not mandatory for replication.

f you rename the design-time file of the dimension calculation view without renaming the runtime view and adjusting the reference:

Building the dimension view as a single object (A) is successful:This operation affects only the renamed file and does not impact other dependent objects.

Building the entire SAP HANA database module (B) is also successful:The module rebuild adjusts references at the runtime level for all objects, ensuring consistency.

The key steps to implement currency conversion in a calculation view are:

Assign Semantic Type:Ensure that the column has the correct semantic type for currency conversion.

Enable the Measure for Conversion:Mark the measure as convertible.

Choose Client, Source, and Target Currencies:Define the currencies involved in the conversion.

Choose Conversion Date and Rate Type:Specify the date and the type of conversion rate (e.g., average, spot rate).

This structured process ensures accurate and consistent currency conversions in your data models.(Reference: SAP HANA Currency Conversion Guide)

The input parameters of calculation view B might not be proposed as source parameters because they are already mapped in another calculation view. SAP HANA restricts the re-mapping of input parameters that have already been assigned to maintain consistent logic and avoid conflicts. When input parameters are pre-mapped in one calculation view, they cannot be reused as source parameters elsewhere without unlinking the prior mapping.

For a calculation view of typeCUBE, the default top view node is theAggregationnode. This node summarizes data based on specified grouping and performs aggregations, making it suitable for analytical purposes and star schemas.

TheKeep Flagproperty in an aggregation node ensures that columns not directly requested by a query are still included in the calculation process if they are critical for the correctness of the result. For example, these columns may serve as grouping or filter criteria in intermediate processing stages, even if not explicitly displayed in the final query output.

TheOPTIMIZED linked databasefeature improves access to remote objects:

A. The metadata of remote tables is cached on the target system: This reduces the overhead of fetching metadata repeatedly.

C. The source and target system must be SAP HANA: This feature is designed specifically for SAP HANA systems for seamless integration.

Hidden virtual tables (B) are not automatically created, and explicit database names (D) are not required.

Nesting flowgraphs provides several advantages:

A. To reduce flowgraph maintenance: Nested flowgraphs promote reusability, reducing redundancy and simplifying maintenance.

C. To improve flowgraph performance: By nesting, you can modularize complex processes, optimize individual components, and enhance overall performance.

Additional node types (B) or simultaneous flowgraph execution (D) are not specific benefits of nesting.

To identify companies that sold products in both January and February, anIntersect Nodeis optimal. It compares two datasets and retrieves only the records that exist in both. In this scenario, the intersect node ensures that only companies with sales in both months are included in the output.

TheHidden Columnscheckbox in the semantics node is used for the following reasons:

C. To ensure specific columns are NOT exposed to the reporting tool: This prevents unwanted columns from appearing in the reporting layer while retaining their use internally within the calculation view.

D. To remove a column that is also used as a Label column: This hides columns used only for labeling purposes from being directly exposed in the output.

The generated input parameter of the interface view allows the user to select whether to run a query on the snapshot table or the original calculation view. This capability provides flexibility, enabling users to choose between querying live data or using static data for consistent results, especially when snapshots are scheduled at specific intervals.

When creating a calculation view that accesses a table in an external schema:

A. Synonym: Synonyms act as aliases to access external schema objects. They are required to integrate external tables into the calculation view.

D. Authorization: You need appropriate schema authorizations to access the external table through the synonym.

A remote source (B) is used for accessing remote systems, and an SQL view (C) is not necessary for this scenario.

TheDynamic Joinoption in SAP HANA calculation views enables flexibility when joining tables with multiple columns. The reasons for enabling it include:

B. To allow data analysis at different levels of granularity with the same calculation view: Dynamic joins adjust to the query’s granularity requirements, enabling analysis at various levels without redesigning the calculation view.

D. To ensure that the join execution uses only the join columns requested in the query: This ensures efficient execution by only processing the relevant columns, reducing unnecessary computations.

If Table B is not pruned in a referential join, the possible issues could be:

C. The Keep flag is activated for the Customer column: This prevents pruning by forcing the inclusion of the column in query execution.

D. Integrity constraint is set to RIGHT: This setting implies that Table B data must always be considered in the join, disabling pruning.

Pruning depends on join conditions and flags; ensuring no unnecessary constraints is essential for proper optimization.

SQL expressions in a calculation view are used for dynamic data transformations and filtering. They can:

A. Generate a restricted column: Apply conditions to create columns with restricted values.

B. Define a filter: Apply SQL conditions to filter data dynamically.

C. Generate a calculated column: Derive new column values using calculations or expressions.

SQL expressions are not typically used for creating hierarchies (D) or currency conversion (E); these are handled by specific features or nodes in SAP HANA calculation views.

To fine-tune performance (B):Implementing SQL in calculation views can help optimize performance by leveraging advanced SQL features and minimizing unnecessary data movement.

To define dynamic analytic privileges (D):SQL enables the implementation of conditions for dynamic analytic privileges, ensuring fine-grained and context-sensitive data access.

Options A and C are less relevant as SQL is not primarily for expanding consumption possibilities or implementing functions, which are handled by other mechanisms in SAP HANA.

Avoid defining joins on calculated columns (A):Joins on calculated columns can significantly impact performance because they require calculations before the join operation. It is better to minimize such scenarios.

Include all data flow logic within one calculation view (B):Consolidating logic within a single calculation view reduces complexity and improves maintainability, avoiding unnecessary data movement across multiple views.

Options C and D are less optimal because defining filters or aggregations on calculated columns can increase the computational overhead.

The simplest approach to create the required output from the provided table is to implement aUnion Nodein the calculation view and map each year as a separate column. This method efficiently aligns data across different columns without needing extensive calculations or additional filter expressions. It provides a structured output while minimizing complexity in the model.(Reference: SAP HANA Calculation View Modeling)