Pass the IBM Certified Developer - Cognos Analytics V11.1.x C1000-065 Questions and answers with ExamsMirror

Compare Card in Exploration: In IBM Cognos Analytics Explorations, a Compare card is used to interactively compare data across visualizations.

Interactive Comparison: This card allows users to set different filters on two visualizations and compare the results side by side. This interactive feature helps in identifying trends and differences between the datasets.

Use Case: The Compare card is particularly useful for scenario analysis, where different conditions or filters are applied to see how they affect the data.

Reference: IBM Cognos Analytics V11.1.x documentation describes the Compare card feature in Explorations, emphasizing its role in facilitating interactive data comparison across multiple visualizations with varying filters.

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.

In IBM Cognos Analytics V11.1.x, before you can modify the text item in a list column title or the data in the column body of a list object, you need to unlock the report. Here are the steps:

Open the Report: Open the report in Cognos Analytics Report Studio.

Lock Page Objects: By default, page objects are locked to prevent accidental changes.

Unlock Page Objects: Click on the "Lock Page Objects" icon in the toolbar to unlock the report. This allows you to make changes to individual cells within the report.

Select and Edit: Once unlocked, select the desired cell within the list object. You can then change the text item or modify the data format as required.

Unlocking the report ensures that you can safely make modifications without impacting other report elements.

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.

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.

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.

Query Performance: Enhancing query performance involves various optimization techniques.

Avoid Functions in Filters: Using functions in filters can lead to slower query performance because functions often require additional computation and can prevent the database from using indexes efficiently.

Best Practices: It is recommended to simplify filters and avoid complex functions to ensure queries run faster.

Reference: IBM Cognos Analytics V11.1.x documentation suggests avoiding the use of functions in filters as a best practice for improving query performance.

PowerPlay Studio: This tool allows developers to create and publish PowerCubes for end-user access and analysis.

Framework Manager: Used for creating and publishing packages, including those based on PowerCubes, making them available to end users.

Transformer: A tool specifically designed to create and manage PowerCubes. After creating a cube, it can be published and made available to users.

Cognos Documentation: The IBM Cognos Analytics V11.1.x documentation outlines the roles of these components in the development and deployment of PowerCubes, emphasizing their interconnectivity and usage.

Jupyter Notebook: This is a widely used open-source web application in the data science community.

Functionality: It enables users to create and share documents that include live code (in various programming languages like Python), equations, visualizations, and narrative text.

Integration with Cognos: In Cognos Analytics, Jupyter Notebooks can be integrated to perform advanced data analysis, leverage machine learning libraries, and present findings interactively.

Reference: The IBM Cognos Analytics V11.1.x documentation describes Jupyter Notebooks as a tool for creating interactive and shareable documents, highlighting their use in combining code execution, data analysis, and explanatory text.

Widgets Panel: The widgets panel in Cognos Analytics provides various elements to enhance the look and feel of dashboards and stories.

Image Library: Administrators can make an Image library tab available in the widgets panel, allowing developers to add images from a predefined collection.

Customization: This feature enables developers to use organizational assets and ensures consistency in visual elements used across different reports and dashboards.

Reference: IBM Cognos Analytics V11.1.x documentation describes the functionality of the widgets panel and the availability of an Image library tab managed by administrators.