C_SAC_2402 Practice Exam Questions with Answers SAP Certified Associate - Data Analyst - SAP Analytics Cloud Certification

Version management in SAP Analytics Cloud stories requires a Planning model. This feature enables users to create and manage different versions of their data, such as budget, forecast, and actual versions. Planning models provide the necessary structure and functionality for versioning, allowing for comparisons and what-if analyses within the story.

References:

• SAP Analytics Cloud Help Documentation: Version Management in Planning
• SAP Analytics Cloud User Guide: Using Planning Models for Versioning

To retain column headers visible when scrolling down in a long table in SAP Analytics Cloud, you should enable "Keeping member names visible" and use the "Freeze Up to row" feature. "Keeping member names visible" ensures that headers remain on the screen as you scroll, while "Freeze Up to row" allows you to specify how many top rows (including the headers) remain fixed during vertical scrolling, enhancing table readability.

References:

• SAP Analytics Cloud Help Documentation: Table Configuration and Customization
• SAP Analytics Cloud User Guide: Enhancing Table Navigation and Readability

To improve the performance of advanced data actions in SAP Analytics Cloud, it's advisable to use fewer MEMBERSET statements, FOREACH functions, and IF statements. MEMBERSET statements can be resource-intensive as they generate sets of members for processing. Minimizing their use can reduce the computational load. Similarly, FOREACH functions, which iterate over sets of members, can significantly impact performance if used extensively. Reducing the number of IF statements can also help, as each condition evaluation adds to the processing time. Streamlining these elements in your scripts can lead to more efficient execution of advanced data actions.

References:

• SAP Analytics Cloud Help Documentation: Optimizing Advanced Data Actions
• SAP Analytics Cloud User Guide: Best Practices for Script Performance

In an analytic data model within SAP Analytics Cloud, the automatically created dimension type that you can delete is the Generic dimension. This type of dimension is typically used for custom or ad-hoc categorizations and, unlike system-generated dimensions like Date or Version, can be modified or removed as per the specific needs of your data model and analysis requirements.

References:

• SAP Analytics Cloud Help Documentation: Data Model Dimensions
• SAP Analytics Cloud User Guide: Managing Dimensions in Analytic Models

A blank planning version in SAP Analytics Cloud can be created within the Version Management feature. This area of the platform allows users to manage different versions of their data, such as budgets, forecasts, and what-if scenarios. Creating a blank version provides a clean slate for planning activities, without pre-existing data, enabling users to start fresh with their assumptions and inputs.

References:

• SAP Analytics Cloud Help Documentation: Version Management in Planning
• SAP Analytics Cloud User Guide: Creating New Versions for Planning

In SAP Analytics Cloud Data Analyzer, you can use various data sources to analyze your data in a tabular, ad-hoc reporting environment. Among the supported data sources are SAP HANA views, which provide real-time access to HANA calculations and data models; SAP Datasphere models, which allow you to leverage data across your enterprise landscape within SAP Datasphere; and SAP BusinessObjects Universes, which enable semantic layers built on various data sources for complex reporting needs.

References:

• SAP Analytics Cloud Help Documentation: Data Analyzer
• SAP Analytics Cloud User Guide: Supported Data Sources for Data Analyzer

To combine two dimensions, Firstname and Lastname, into a single dimension displaying as Lastname, Firstname in a live data model, you should create a calculated dimension in the data model. This calculated dimension will concatenate the two fields into one, according to the specified format. This approach allows for the creation of a new dimension that can be used across various reports and analyses within the model, maintaining the integrity of the original dimensions.

References:

• SAP Analytics Cloud Help Documentation: Creating Calculated Dimensions
• SAP Analytics Cloud User Guide: Data Modeling Best Practices

In SAP Analytics Cloud, enabling Advanced Mode in story design is necessary for activities that involve custom development or advanced integration, such as adding JavaScript to a button for custom interactions or behaviors, and adding a custom widget, which allows for the integration of bespoke visualizations or functionalities that are not available out-of-the-box. These features require a deeper technical engagement, hence the need for Advanced Mode.

References:

• SAP Analytics Cloud Help Documentation: Advanced Story Design Features
• SAP Analytics Cloud User Guide: Custom Widgets and JavaScript Functions

In the context of creating an allocation step to distribute expenses from the HR cost center to operating cost centers in SAP Analytics Cloud, the "Driver" dimension setting is crucial. This setting determines the basis or criteria on which the distribution is calculated and applied to each operating cost center. For instance, the driver could be the number of employees, square footage, or any other relevant metric that justifies the distribution of costs. By defining a driver, you ensure that the allocation of expenses is proportional and fair based on the selected criteria.

References:

• SAP Analytics Cloud Help Documentation: Allocation Steps in Planning
• SAP Analytics Cloud User Guide: Using Drivers for Allocation

In SAP Analytics Cloud stories, conditional formatting can be applied to Table and Chart elements. This feature allows users to visually highlight data points based on specific conditions, such as thresholds, ranges, or comparisons, making it easier to identify trends, outliers, or areas of interest within the data presented in tables and charts.

References:

• SAP Analytics Cloud Help Documentation: Conditional Formatting
• SAP Analytics Cloud User Guide: Applying Conditional Formatting to Tables and Charts

In SAP Analytics Cloud, a Time Series Forecast predictive scenario can write back to a planning model. Time Series Forecasting leverages historical data to predict future values over a specified time horizon, using statistical or machine learning methods. This feature is particularly useful in planning and forecasting processes, where future values are predicted based on past trends and seasonality. The ability to write these forecasts back into a planning model allows for the integration of predictive insights into the planning process, enhancing decision-making and strategic planning.

References:

• SAP Analytics Cloud Help Documentation: Predictive Scenarios and Planning
• SAP Analytics Cloud User Guide: Time Series Forecasting in Planning Models

Input controls in a story in SAP Analytics Cloud can be used for changing dimensions or measures displayed in a table and for filtering data on a page. Input controls provide a way for users to interactively modify the view of the data, such as selecting which dimensions or measures to display, or filtering the entire page's content based on selected criteria, enhancing the interactivity and flexibility of data analysis within stories.

References:

• SAP Analytics Cloud Help Documentation: Input Controls in Stories
• SAP Analytics Cloud User Guide: Using Input Controls for Data Interaction

In SAP Analytics Cloud, a data model must contain at least "Dimensions" and "Measures" to be functional. Dimensions are the qualitative aspects of the data (e.g., time, geography, product categories) that provide the context for analysis. Measures, on the other hand, are the quantitative data points (e.g., sales, costs, quantities) that are analyzed within the context provided by dimensions. Both are fundamental components of a data model, enabling structured data analysis and reporting.

References:

• SAP Analytics Cloud Help Documentation: Building Data Models
• SAP Analytics Cloud User Guide: Understanding Dimensions and Measures in Models