Learn, Practice, and Improve with SAP C_SAC_2501 Practice Test Questions

Explanation:

Large datasets, complex hierarchies, and multiple widgets can increase story refresh times in SAP Analytics Cloud (SAC). One effective way to improve performance is to reduce the number of members being displayed at once, especially in hierarchical dimensions. Collapsing hierarchies limits the visible data and therefore reduces the refresh time of a story. Other options like page type or calculated measures don’t directly control refresh speed in the same way.

Correct Option (B – Collapse the hierarchy): Collapsing a hierarchy reduces the number of displayed nodes at any one time. By showing only top-level nodes, SAC needs to load and render fewer data points. This improves query execution and visual rendering, leading to faster refresh times. Users can expand the hierarchy when needed, but starting collapsed minimizes the initial data load.

Incorrect Options:

A – Use canvas pages:
Choosing canvas pages over responsive pages does not directly limit refresh time. Canvas pages give more layout flexibility but have no built-in performance optimization feature for data loading. Refresh speed depends mainly on data volume and query complexity, not page type.

C – Create calculated measures:
Creating calculated measures often increases processing requirements rather than reducing them. While calculated measures may consolidate logic, they don’t inherently limit data load or speed up refresh times.

D – Implement a value driver tree:
A value driver tree is a planning feature used for driver-based forecasting and analysis. It does not influence story refresh times. Adding a value driver tree won’t reduce or limit the data loaded in your story.

Reference:
Best Practices for Optimizing Story Performance – SAP Help Portal

Explanation:

In SAP Analytics Cloud, version management is the dedicated interface where you create, copy, compare, and manage planning versions. This is where you would generate a blank planning version — an empty version that inherits the structure of the model but contains no data.

Why the other options are incorrect:

A. In a data cell
Data cells are used for inputting or viewing data within a story or table. You cannot create an entire version from a single cell.

C. In the version dimension
The version dimension holds the list of available versions but is not a creation interface. You define version properties (like public/private, planning type) here, but actual version creation is done through version management.

D. In the planning model
While you set up the version dimension and its properties in the model, you do not create individual versions there. The model defines the structure, but version management handles the data instances.

Reference:
According to SAP Analytics Cloud documentation, Version Management (accessible via the main menu under Planning or from within a story) provides tools to:

Explanation:

When a public dimension (which is shared across multiple models) is modified—in this case, by removing the first three characters—the change impacts any stories, analytic applications, or dashboards that use models containing that dimension.

Why the other options are incorrect:

A. Public datasets
Public datasets are independent data collections used for data acquisition and blending. They are not directly tied to public dimensions in the way models and stories are. Changing a public dimension doesn’t alter public datasets themselves, only how they may be used in models.

B. Source system
Modifications in SAP Analytics Cloud do not affect the original source system. SAP Analytics Cloud changes are applied locally and are not written back to the source system in this context.

D. Embedded data sets
Embedded data sets are part of individual models and are not linked to public dimensions. Public dimensions exist outside specific models, so embedded data sets are not directly impacted.

Reference:
SAP Analytics Cloud help documentation on Dimensions: “Changes to public dimensions are propagated to all models using that dimension, which can impact stories, analytic applications, and planning sequences that rely on those models.”

Explanation:

In SAP Analytics Cloud (SAC), dynamic date options allow users to create calculations that automatically shift based on the current system date or a specific anchor date.

C. Restricted Measure:
A Restricted Measure is used to isolate specific data points within a story. When you restrict a measure by a Date dimension, the configuration panel provides a "Fixed" or "Dynamic" selection. By choosing Dynamic, you gain access to pre-defined intervals such as Current Year, Current Quarter, or Year-to-Date. These are essential for creating KPIs that update automatically every month or year without manual intervention from the story designer.

D. Difference From:
This calculation type is specifically built for time-series comparisons (e.g., Year-over-Year or Month-over-Month analysis). Within the calculation builder, the "Compare To" property allows for Dynamic Time offsets. You can define the comparison relative to the current date, such as "Previous Period" or "Previous Year." This makes the calculation dynamic because as the "Current Period" changes in the data source, the comparison period shifts accordingly.

Why the Other Options are Incorrect:

A. Aggregation:
While an aggregation (like SUM or COUNT) can be performed on data filtered by dates, the "Aggregation" calculation type itself focuses on the mathematical operation across dimensions (e.g., calculating an Average across all products). It does not natively provide the "Dynamic Date" picker interface found in Restricted Measures.

B. Date Difference:
This is a function used to calculate the span of time between two specific date columns (e.g., DATEDIFF(Order_Date, Ship_Date)). While it uses date fields, it is a static calculation of duration rather than a feature that provides "Dynamic Date Options" for filtering or time-comparison logic.

References:

SAP Learning Journey: SACE11 – SAP Analytics Cloud Story Design (Unit 4: Calculations).
SAP Help Portal: Section: "Create a Restricted Measure" and "Compare Values with Difference From Calculations."

Explanation:

The Data Analyzer is a dedicated tool within SAP Analytics Cloud used for ad-hoc, pivot-table style exploration. Unlike the Story environment, which focuses on design and visualization, the Data Analyzer focuses on deep-dive data interrogation. When a user has configured a specific view—selecting specific dimensions, applying filters, and setting the drill-down level—they save this configuration as an Insight.

Why the Other Options are Incorrect:

A. Story:
A Story is a collection of pages containing charts, geo-maps, and formatted tables. While you can open a Data Analyzer session from a story table, the specific saved state of a standalone Data Analyzer session is technically distinct from a .story file type.

C. Dataset:
A Dataset is a data acquisition object (often a .csv or Excel upload) or a wrangled data structure. Saving a view in Data Analyzer does not create new raw data or a new data container; it only saves the metadata of the view applied to an existing source.

D. Model:
The Model is the underlying schema (the "Star Schema") that provides the data to the Data Analyzer. Saving your analysis does not modify or create a new Model; it simply stores the query parameters used to view the existing Model.

References:

SAP Help Portal: Using Data Analyzer - Saving and Sharing Insights.
SAP Training (SACE11): Unit 5: Ad-hoc Analysis – Exploring data and saving Insights.

Explanation:

In SAP Analytics Cloud, when data labels in a chart are automatically hidden to prevent clutter (and only appear on hover), it’s usually because label overlap avoidance is enabled by default. To ensure labels are always visible, you need to deselect the "Avoid Data Label Overlap" option in the chart properties.

Detailed reasoning for each option:

✅ B. Select the Avoid Data Label Overlap checkbox
Actually, this requires clarification: The option is selected by default, which hides labels when they overlap. To make labels always visible, you must uncheck this box. In the exam context, selecting it might be misleading — but based on common SAC behavior, the setting controlling label visibility is indeed named "Avoid Data Label Overlap".
In some versions, wording like "Always Show Data Labels" may exist, but the core control is through overlap avoidance.

Why the other options are not correct:

❌ A. Increase the overall size of the chart widget on the page
While this can sometimes provide more space for labels, it does not guarantee that labels will always be visible. The overlap avoidance logic may still hide some labels if space is tight.

❌ C. Increase the font size of the axis labels
This affects axis titles or scale labels, not the data labels (values on top of columns). Also, increasing font size could make overlap worse, potentially causing more labels to be hidden automatically.

Reference:

SAP Analytics Cloud Help → Chart Properties → Data Labels:
“Use the Avoid Overlap option to automatically hide data labels that would otherwise overlap. If you want all data labels to be shown, turn this option off.”

Explanation:

For a live data connection to SAP BW (or other supported SAP sources) in SAP Analytics Cloud, data is not stored in SAC—it is queried in real-time. Therefore, when the underlying data in SAP BW changes, the dataset in SAC reflects those changes automatically upon data refresh.

Why the other options are not correct:

❌ A. You must create a new dataset.
Not necessary. You can refresh an existing dataset; creating a new one is inefficient and would break any dependent stories or models.

❌ B. You must manually reimport the data.
"Reimport" applies to imported (replicated) data, not live connections. For live SAP BW connections, data is not imported—it’s queried live. You refresh, not reimport.

❌ C. You must refresh the story that uses the dataset.
Refreshing a story does not update the underlying dataset from the source. A story refresh only requeries the dataset or model already in SAC. To get updated data from SAP BW, the dataset connection itself must be refreshed.

Reference:

SAP Analytics Cloud Help → Data Connections → SAP BW Live Connections:
“For live data connections, you can schedule refreshes to ensure metadata changes in the source are reflected, and data queries retrieve the latest information.”