C1000-065 Sample Questions Answers

When the Drill-through target type is set to Bookmark in IBM Cognos Analytics V11.1.x, the following types of saved report outputs can be used:

HTML:

Interactive Output: HTML outputs are interactive and support bookmarks, allowing users to navigate to specific sections within the report.

Usability: Ideal for web-based viewing and interaction.

PDF:

Static Output: PDF outputs support bookmarks and provide a static, paginated format that is useful for printing and sharing.

Accessibility: Bookmarks in PDFs enhance navigation within long documents.

These output types leverage the bookmark functionality to improve navigation and user experience.

Drill-through Definition: Drill-throughs in Cognos Analytics allow users to navigate from one report or visualization to another, typically to see more detailed information.

Passing Data Points: Data points can be passed to the target Drill-through provided the data sources have matching values. This ensures continuity and relevance in the data being analyzed.

Targeting Other Dashboards and Reports: Developers can set up Drill-throughs to link to other dashboards or reports, facilitating deeper analysis and better data exploration.

Cognos Documentation: IBM Cognos Analytics V11.1.x documentation provides guidelines on creating and managing Drill-throughs, including passing parameters and targeting various types of reports and dashboards.

Interactive Performance Assistant: This tool in IBM Cognos Analytics V11.1.x provides real-time performance monitoring and analysis for reports.

Enabling the Assistant: By enabling the interactive performance assistant, users can gather detailed performance metrics as the report runs, which helps identify bottlenecks and areas for optimization.

Benefits: This tool provides insights into query execution times, rendering times, and resource usage, enabling developers to make informed decisions to improve report performance.

Reference: The IBM Cognos Analytics V11.1.x documentation outlines how to enable and use the interactive performance assistant for investigating and improving report performance.

Data Preparation: IBM Cognos Analytics provides built-in capabilities to clean and transform data within data modules.

Prepare Menu: The 'Prepare' menu item allows developers to apply various transformations, including trimming spaces and converting text to lowercase, directly to data items.

Cleaning Data: By using the 'Prepare' menu, developers can make data more readable and suitable for reporting without needing additional calculations in the report itself.

Reference: The IBM Cognos Analytics V11.1.x documentation details the use of the 'Prepare' menu for data preparation tasks, ensuring data is cleaned and formatted appropriately within data modules.

To create a Layout Component Reference in a report in IBM Cognos Analytics V11.1.x, you need to provide the "Name" property. Here are the steps:

Define Component: Identify the component you want to reference in your report layout.

Set Name Property: Assign a unique name to the component in its properties. This name will be used to reference the component.

Create Layout Component Reference: In the report where you want to use the component, add a Layout Component Reference and specify the name of the original component.

Reference the Component: The referenced component will be displayed in the new location, allowing you to reuse layout elements across multiple reports.

Using the "Name" property ensures that components can be easily referenced and maintained.

Multidimensional Report Writing: This approach leverages MDX (Multidimensional Expressions), which is optimized for querying multidimensional data.

Flexibility of MDX: MDX's flexibility allows complex queries to be written more efficiently, reducing the need for multiple queries and unions.

Query Maintenance: This reduces the maintenance burden, as fewer queries are needed and the queries are more straightforward to manage.

Reference: IBM Cognos Analytics V11.1.x documentation emphasizes the advantages of using MDX for complex queries in multidimensional report writing, particularly in minimizing the number of required queries and unions.

Default Measure Property: Changing the Default measure property in a Crosstab impacts how measures are displayed.

Replacing Existing Measures: If a measure is already set on the Crosstab edges, changing the Default measure will replace the existing measure with the new Default measure.

Crosstab Updates: This change updates the Crosstab intersections to reflect the new Default measure, altering the displayed values accordingly.

Reference: The IBM Cognos Analytics V11.1.x documentation provides comprehensive details on Crosstab properties and the implications of modifying the Default measure, ensuring accurate data representation in reports.

Regarding custom sorts in IBM Cognos Analytics dashboards, here’s the correct information:

Creating Custom Sorts:

Applicable Data Types: Custom sorts can be created on dimensions and categorical data but not on measures. Measures are numerical values used for calculations and aggregations, and sorting them customly is not supported in the same way as categorical data.

Implementation:

Procedure: To create a custom sort, select the field from the source pane, right-click, and choose the sorting options from the properties menu. Specify the custom sort order as required.

Limitations:

Non-measures Only: Ensure you are applying custom sorts to non-measure fields, such as dimensions or attributes, to control the order in which data is displayed in visualizations.

Custom sorting enhances the presentation and analysis of data by allowing users to define specific order criteria.

Using Data Sets: To use a Data set as a data source in a report, it needs to be added to a Data Module.

Data Module Integration: Adding the Data set to a Data Module integrates it into the Cognos environment, making it accessible for report development.

Procedure: Developers can create or modify a Data Module to include the Data set, which then becomes available for use in reports.

Reference: The IBM Cognos Analytics V11.1.x documentation explains the process of adding Data sets to Data Modules, enabling their use as data sources in reports.

Layout Component Reference: This feature in IBM Cognos Analytics allows developers to reference existing report objects within the same report or across different reports.

Reuse for Consistency: By referencing existing components, developers ensure consistency in design and functionality across multiple reports.

Efficiency: This method reduces the effort needed to recreate similar report objects and facilitates easier maintenance and updates.

Reference: According to IBM Cognos Analytics V11.1.x documentation, Layout Component References are intended to streamline report development by allowing the reuse of report objects, thereby enhancing consistency and efficiency.

Cognos Analytics Data Set: A data set in Cognos Analytics is an extract from a package or data module.

Storage and Refresh: These extracts are compressed, stored locally, and can be refreshed either periodically or manually, depending on the requirements.

Use Case: Data sets are used to improve performance by reducing the need for repeated database queries and enabling offline access to the data.

Reference: IBM Cognos Analytics V11.1.x documentation details the nature of data sets, highlighting their extraction process, storage, and refresh capabilities for enhanced performance and usability.

Enabling the local cache property on a query in IBM Cognos Analytics V11.1.x has the following implications:

Improved Performance:

Data Caching: When local cache is enabled, data is cached locally, which can improve performance by reducing the need to repeatedly fetch data from the source.

Efficiency: This caching mechanism speeds up report execution and interaction times, especially when dealing with large datasets or complex queries.

Batch Reports:

Support: Local caching is particularly beneficial for batch reports, where multiple runs can leverage the cached data to enhance performance.

Impact on Scalability:

Scalability Considerations: While caching can improve performance, it might impact the scalability of the report depending on the volume of data and the frequency of cache refreshes.

Enabling local cache optimizes report execution by leveraging previously fetched data, thus enhancing user experience.

Custom Sorting: In IBM Cognos Analytics dashboards, custom sorting allows developers to manually define the order of columns in visualizations.

Manual Ordering: By using custom sorting, the developer can specify the exact order in which columns should appear, overriding any automatic sorting.

Implementation: This is done by accessing the sort options for the visualization and choosing the custom sort option, where the desired order can be set.

Reference: IBM Cognos Analytics V11.1.x documentation details the process of using custom sorting to manually order columns in a visualization, ensuring that the display order meets specific requirements.

Represents Property: In Cognos Analytics, the Represents property helps define how an attribute should be interpreted and visualized.

Geographic Location: Setting the Represents property of an attribute to Geographic location signals to Cognos that this data should be visualized on a map by default.

Implementation: This ensures that when a user drags this attribute onto a dashboard, Cognos will automatically use the Map visualization.

Reference: According to the IBM Cognos Analytics V11.1.x documentation, setting the Represents property to Geographic location is the correct method to ensure default map visualization for geographic data.

When using an OLAP data source, summaries that use 'For' clauses might give incorrect results due to the nature of OLAP data sources. Here’s why:

OLAP Data Structure:

Lack of Detail Rows: OLAP data sources are designed for multidimensional analysis and do not contain detail rows like relational databases. They store aggregated data at different levels of a hierarchy.

Implications for Summaries: Since the 'For' clause is used to generate summaries based on detail rows, applying it to an OLAP data source, which lacks these detail rows, can lead to incorrect or unexpected results.

Summarization Logic:

Aggregation Context: In OLAP, summarization is performed based on predefined hierarchies and aggregation rules, not on individual detail rows.

Correct Approach: When working with OLAP data, it’s essential to use functions and summarization techniques that are compatible with its structure.

Understanding the differences in data structures between OLAP and relational sources is critical for accurate report development.