In IBM Cognos Analytics V11.1.x, dimensional functions should be used in a report's Query calculation when working with a dimensional or dimensionally-modeled data source. Here’s why:
Dimensional Data Sources:
Structure: Dimensional data sources are organized into dimensions, hierarchies, and measures. These structures support advanced analytical capabilities such as drill-down and roll-up.
Dimensional Functions: Functions such asmember,ancestor,children, etc., are specifically designed to navigate and manipulate the hierarchical data structures in dimensional sources.
Query Calculations:
Contextual Calculations: Dimensional functions allow for context-aware calculations, leveraging the inherent structure of the data source. This ensures that calculations respect the dimensional context and hierarchy.
Analytical Depth: Using dimensional functions enables deeper analytical capabilities, such as performing relative date calculations, time series analysis, and hierarchical aggregations.
Dimensional functions are essential for harnessing the full analytical power of dimensionally-modeled data sources.
[: IBM Cognos Analytics Framework Manager and Report Studio User Guides, , ]
Question 2
Which of the following can result in poor report performance?
Options:
A.
reports with filters
B.
models with outer joins and cross joins
C.
queries with database only processing
D.
an optimized metadata model
Answer:
B
Explanation:
Understanding Joins: Outer joins and cross joins often result in large intermediate result sets. This can slow down query performance due to the increased data processing required.
Outer Joins: These include rows that do not have matching keys in the joined tables, which means more data to process and potentially more I/O operations.
Cross Joins: These produce Cartesian products of the involved tables. If the tables are large, the resulting dataset can be enormous, leading to significant performance degradation.
Cognos Documentation: The IBM Cognos Analytics V11.1.x documentation advises optimizing join conditions and limiting the use of complex joins such as outer and cross joins to enhance performance.
Question 3
Which statement is true when adding a data source in a dashboard?
Options:
A.
Framework Manager Packages, Data Modules and Data sets are the only three types of data sources that can be used when creating a dashboard.
B.
Only data sources that have been added to a Data Module can be used as a data source.
C.
Framework Manager Packages, OLAP Packages, Data Modules, Data sets and CSV files can all be used when creating a dashboard.
D.
Once a data source has been added it can only be removed by deleting all data sources within the dashboard.
Answer:
C
Explanation:
Supported Data Sources: IBM Cognos Analytics supports various data sources for creating dashboards, including Framework Manager Packages, OLAP Packages, Data Modules, Data sets, and CSV files.
Flexibility: This wide range of supported data sources provides flexibility for users to integrate different types of data into their dashboards.
Data Source Addition: Users can easily add and manage these data sources within the dashboard creation interface.
Reference: The IBM Cognos Analytics V11.1.x documentation lists and explains the types of data sources that can be used when creating dashboards, confirming the inclusion of Framework Manager Packages, OLAP Packages, Data Modules, Data sets, and CSV files.