SAP Certified Application Associate - SAP HANA 2.0 SPS06 - C-HANAIMP-18무료 덤프문제 풀어보기

A. The code should modify data in a table.

B. Optimal performance is a priority.

C. You want to create a dynamic analytic privilege.

D. A temporary table must be created within the code.

E. You need to use conditional logic.

A. To push down filters to the lowest level calculation views

B. To assign variables to one or more attributes

C. To convert the data types of input parameters

D. To pass variable values to external value help views

A. A measure that can only be displayed by those with necessary privileges.

B. A measure that is filtered by one or more attribute values.

C. A measure that can be consumed by a CUBE and not a DIMENSION.

D. A measure that cannot be referenced by a calculated column.

A. Specify the join cardinality

B. Use an inner join

C. Limit the number of joined columns

D. Define join direction in a full outer join

A. Enable the measure for conversion Choose client, source and target currencies Choose conversion date and rate type Assign the conversion rule to your calculation view

B. Assign semantic type Choose client, source and target currencies Choose conversion date and rate type Define an expression in a calculated column

C. Enable the measure for conversion Choose client, source, and target currencies Choose conversion date and rate type Build the conversion rule

D. Assign semantic type Enable the measure for conversion Choose client, source and target currencies Choose conversion date and rate type

A. You did not define any columns in the cache setting.

B. You did not define a filter in the cache setting.

C. The cache data retention period has expired.

D. The query requests only a subset of the cached results.

A. Stored aggregates

B. Indexes

C. Partitions

D. Views

A. Avoid defining joins on calculated columns.

B. Model star schemas using a sequence of join nodes.

C. Include all data flow logic within one calculation view.

D. Aggregate at the lowest possible node.

A. To enable partitioning of the table across different storage tiers

B. To evenly distribute the data across all available server nodes

C. To improve read performance when the table is accessed by simultaneous applications

D. To implement a table that combines the features of row and column store