In the SAP Analytics Cloud data preparation environment (data wrangler), both the Custom Expression Editor and the Transform bar are used to modify and cleanse data within a dataset. The Custom Expression Editor allows for the creation of complex formulas using functions like REPLACE() or SUBSTRING() to programmatically remove specific characters from a column. The Transform bar offers smart, context-aware suggestions. For instance, by selecting a value in a column, it can suggest a "Replace" transformation, which can be configured to replace certain characters with an empty string, effectively deleting them.

B. Formula bar: This is used within a story (e.g., in a table widget) to create dynamic, front-end calculations for visualization, not to permanently transform the underlying dataset.

C. Calculation editor: This is used within the Modeler to create calculated measures or dimensions. It defines analytical logic for the model, not for cleansing the raw source data.

1. SAP Help Portal

SAP Analytics Cloud - Applying Custom Expressions to Transform Data: "You can create a custom expression to transform your data... The custom expression editor lets you create formulas using a combination of columns

functions

and operators." This document details the use of the editor for data manipulation

which includes deleting characters via functions.

2. SAP Help Portal

SAP Analytics Cloud - Applying Transformations in the Data Wrangling View: "The smart transformation bar suggests transformations that you can apply to your data." This page describes the functionality of the transform bar

which includes actions like "Replace values

" a primary method for deleting characters.

3. SAP Help Portal

SAP Analytics Cloud - Adding Calculations to a Table: "You can add simple calculations directly to a table using the formula bar." This reference clearly places the Formula Bar's function within a story's table

distinguishing it from dataset preparation.

4. SAP Help Portal

SAP Analytics Cloud - Create a Calculation in the Modeler: "You can create calculations in the Calculation Editor... Calculations can be created for measures and dimensions." This source confirms the Calculation Editor is a tool for the modeling environment

not data wrangling.

The SAP Analytics Cloud (SAC) data analyzer is a tool for ad-hoc data exploration. It operates directly on SAC analytic models (D), which act as the semantic layer. These models can be based on various underlying data sources. Among the most prominent and strategic live data sources that are fully supported for use in models explored by the data analyzer are SAP HANA views (B) and SAP Datasphere models (C). These sources allow for real-time, detailed analysis without data replication, which is a primary use case for the data analyzer.

A. SAP Analytics Cloud public dataset: While data analyzer can technically open datasets, public datasets are sample data intended for demonstration or training, not a primary enterprise data source for serious ad-hoc analysis.

E. SAP BusinessObjects Universe: Although a supported connection, it is primarily for leveraging existing legacy assets. SAP's strategic focus for modern analytics, especially with tools like data analyzer, is on native sources like HANA and Datasphere.

1. SAP Help Portal

SAP Analytics Cloud

"Data Analyzer": This official documentation explicitly states that data analyzer is used to get a detailed view of data from a model. It then lists the supported live data sources for these models

including SAP HANA

SAP Datasphere

and SAP BusinessObjects Universe. This supports the inclusion of (B)

(C)

and (D) as the model is the direct object and HANA/Datasphere are key underlying sources.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/05a797a1b151494a926004e9155b07e3.html

2. SAP Help Portal

SAP Analytics Cloud

"Live Data Connections": This page details the types of live connections available. It lists SAP HANA

SAP Datasphere

and SAP S/4HANA as primary live connection types

reinforcing their strategic importance as data sources for all analytical clients

including data analyzer.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/03b44b88052042939e17a0826fecbd03.html

Table formulas in SAP Analytics Cloud are the designated feature for performing calculations at the individual cell level within a table in a story. This functionality allows users to add new rows or columns and then define custom, spreadsheet-like formulas for specific cells, often by referencing other cells. This capability is distinct from model-level or story-level calculations that operate on entire measures, providing granular control for ad-hoc analysis directly within the table visualization.

A. Calculated measures: These are column-level calculations (e.g., [Revenue] - [Cost]) that apply to the entire measure, not to specific, individual cells within a table.

B. Dimension formulas: This is not the correct term for the feature that performs cell-based numeric calculations in a table within an SAC story.

C. Restricted measures: This feature is used to filter a measure's data based on dimension members (e.g., Revenue for a specific region), not to perform a calculation.

1. SAP Help Portal - Adding Formulas to Tables: "You can add a calculation as a new row or column in a table. You can then add a formula to the cells in the new row or column... This is useful for creating custom or ad-hoc calculations in a table." This source directly confirms the use of table formulas for cell-based calculations.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/b5331739975846379a38a87ad36e1b37.html

2. SAP Help Portal - Create Calculated Measures in Stories: "When you add a calculation to a story

you create a new measure... The calculation is applied to the entire column of data for the selected measure." This source differentiates calculated measures as column-level operations.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/093f56a795314c0e834959b5c85a3a10.html

3. SAP Help Portal - Create Restricted Measures in Stories: "When you add a restriction to a story

you create a new measure with data restricted to the values you select... It's a way of filtering the measure by one or more dimension members." This source defines restricted measures as a filtering mechanism.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/d1e4d9977b334c2888a496d12a2e6985.html

In SAP Analytics Cloud (SAC) advanced data action scripts, virtual variables are used to pass values from a story or analytic application into the script. To reference these virtual variables within the script, their names are enclosed by percent signs. The correct syntax is %VariableName%. Therefore, the % character is the designator for a virtual variable member.

B. /: This character is used as the division operator in script formulas.

C. : This character is used as the multiplication operator in script formulas.

D. #: This character is typically used to refer to the unassigned member ([d/Dimension] = #) or as part of a member ID string in a formula, not to designate a variable.

1. SAP Help Portal - SAP Analytics Cloud

Creating an Advanced Data Action Script: "You can use virtual variables to pass values from a story or analytic application to a data action. In the script

you can refer to a virtual variable using the %% syntax."

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/d51ac895168d46769cf3313f3b3a5b52.html (Refer to the section on using script variables).

2. SAP Help Portal - SAP Analytics Cloud

Advanced Formulas for Data Actions: This guide details the syntax and functions available in advanced formulas

confirming the use of standard arithmetic operators like and /

and the specific syntax for member selection

which does not use %.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/15968571b03543359669f46531254f2a.html (Refer to sections on "Syntax in Advanced Formulas" and "Member Expressions").

In SAP Analytics Cloud, the Predictive Planning feature is specifically designed to integrate predictive capabilities with planning models. This feature exclusively uses time series forecasting algorithms to analyze historical data and generate future predictions. The resulting forecast can then be directly written back into a specific version of a planning model. This allows planners to use a statistically generated baseline for their budgets and forecasts, streamlining the planning process. The other predictive scenario types do not have this direct write-back capability to a planning model.

A. Regression: Regression scenarios predict a numerical value but are not designed for the direct write-back integration with planning models that time series forecasting offers within Predictive Planning.

B. Value driver tree: A value driver tree is a manual simulation tool used within planning for "what-if" analysis; it is not a type of automated predictive scenario.

C. Classification: Classification scenarios predict a categorical outcome (e.g., churn/no-churn), which is structurally incompatible with writing back to a numerical measure in a planning model.

1. SAP Help Portal - SAP Analytics Cloud

Predictive Planning: "With the predictive planning features of SAP Analytics Cloud

you can use time series forecasting techniques to fill in the empty cells in your planning tables... You can then write the predictive forecasts back to your private version."

Source: SAP Help Portal

Getting Started with Predictive Planning. (The specific URL changes with updates

but the content is found under the SAP Analytics Cloud > Planning > Predictive Planning section).

2. SAP Help Portal - What Are Predictive Scenarios?: This document outlines the different types of predictive scenarios (Classification

Regression

Time Series). It implicitly distinguishes the application of time series for planning write-back from the other types.

Source: SAP Help Portal

What Are Predictive Scenarios?. (Found under SAP Analytics Cloud > Smart Predict).

3. SAP Learning Hub Courseware (CSAC2501): The SAC400 (SAP Analytics Cloud: Planning) and SACAD1 (SAP Analytics Cloud Administration) courses detail the planning process. They specify that Predictive Planning uses time series forecasting to populate a plan version.

Source: SAP Learning Hub

Course SAC400

Unit on Predictive Planning.

SAP Analytics Cloud (SAC) supports live data connections to a specific set of SAP systems, where data is queried in real-time and remains in the source system. SAP Datasphere is a primary and strategic source for live connections with SAC. This integration is a core component of SAP's Business Technology Platform, allowing for real-time analytics on data models built in Datasphere without data replication. The connection leverages the native capabilities of both cloud solutions for optimal performance and security.

A. SAP ERP Central Component: Direct live connections from SAC to SAP ECC are not supported. Connectivity typically requires an intermediary system like SAP BW/HANA or uses an import (acquired) data connection.

B. SAP SuccessFactors: Connections to SAP SuccessFactors for analytical reporting in SAC are primarily based on import (acquired) data, where data is replicated into SAC, not accessed live.

C. SAP Business ByDesign Analytics: Similar to SuccessFactors, connections from SAC to SAP Business ByDesign are supported via import (acquired) data connections, not live connections.

1. SAP Help Portal - Data Connections – Live: This official documentation lists the systems available for live data connections. SAP Datasphere is explicitly included as a supported source.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/5b45bc5167ce4a21a3324515b2a3c379.html

Section: "Live Data Connections" table.

2. SAP Help Portal - Import Data Connection to SAP ERP: This document clarifies that connections to SAP ERP (which includes ECC) are import-based.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/b33593a359fb4a319a67616811284a7b.html

Section: "Introduction".

3. SAP Help Portal - Import Data Connection to SAP SuccessFactors: This source confirms that connections to SuccessFactors are for importing data.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/b641a2907e794161b7a22f8b687558da.html

Section: "Prerequisites".

Data analyzer in SAP Analytics Cloud is a tool for ad-hoc analysis on a single data source. It allows users to explore data dynamically. Key supported features include the ability to switch between table and chart views for data visualization (B), apply conditional formatting (thresholds) to highlight important data points within the table (C), and create on-the-fly calculations, such as calculated or restricted measures, to derive new insights directly within the analysis environment (E). These capabilities are central to its purpose as a flexible data exploration tool.

A. Linked dimensions: This feature is used for blending data from multiple models within a Story, not a function of the single-source data analyzer tool.

D. Input controls: These are interactive filter widgets added to the canvas of a Story or Analytic Application, not a native feature within the data analyzer interface.

1. SAP Help Portal - Data Analyzer: This official documentation provides an overview of data analyzer's capabilities

explicitly mentioning the ability to "switch between a table and a chart view

" "add calculated measures

" and "apply conditional formatting (thresholds)."

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/136b551cde7941699386d3344385048c.html

2. SAP Help Portal - Adding Calculations in Data Analyzer: This page details the process of creating calculated measures and dimensions within the data analyzer.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/882f238209514840a755091b7f79a675.html

3. SAP Help Portal - Linking Dimensions (Data Blending): This source clarifies that linking dimensions is a feature for Stories to combine data from different models.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/d789379555a74831990205291e765225.html

SAP Analytics Cloud provides two primary methods for connecting to data sources. The Live connection type allows for real-time data access by querying the source system directly without replicating the data into SAP Analytics Cloud. This ensures the data is always current. The Import connection type (also known as an Acquired connection) copies data from the source system and stores it within the SAP Analytics Cloud tenant. This allows for data transformation and enrichment within the SAC modeler but requires scheduled refreshes to keep the data up-to-date.

B. On-premise: This describes the physical location or deployment model of a data source, not a connection type. Both Live and Import connections can be made to on-premise systems.

C. Cloud: This also describes the location of a data source. SAP Analytics Cloud can connect to various cloud systems using either Live or Import connection types.

1. SAP Help Portal - Data Connections in SAP Analytics Cloud: "SAP Analytics Cloud offers two methods for connecting to data sources: Live Data Connections and Import Data Connections." This document explicitly defines the two primary connection types.

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/bda96b394b424318884a369042348942.html

2. SAP Help Portal - Live Data Connections: This page details the Live connection methodology

stating

"With live data connections

your data stays in your source system."

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/200a374c411a491fb850b5329233f213.html

3. SAP Help Portal - Import Data Connections: This page describes the Import connection

explaining

"When you import data into SAP Analytics Cloud

the data is copied and stored in SAP Analytics Cloud."

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/c388f5d7c4b34929959ab36ad75112a6.html

A live data connection in SAP Analytics Cloud establishes a direct link to a source system without replicating or storing the data within the SAC tenant. When a user interacts with a story or model based on a live connection, queries are sent directly to the source system in real-time. The data processing and storage remain entirely within the original source system (e.g., SAP HANA, SAP BW, S/4HANA). This architecture ensures that the data is always current and leverages the security and performance of the underlying source platform.

A. Public dataset: This is a type of data source, not the storage location for a live connection model.

B. SAP Analytics Cloud model: Data is stored in the SAC model only with import (acquired) data connections, where data is copied from the source.

D. Embedded data set: This describes data stored within an SAC artifact, which is characteristic of an import connection, not a live one.

1. SAP Help Portal

"Live Data Connections to SAP HANA": "With live data connections

your data stays in your source system and is not replicated to SAP Analytics Cloud. This means that any data

including sensitive or personal data

is not brought into the cloud."

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/b963593a2e4447258543114a3730884a.html

2. SAP Help Portal

"Data Connectivity – Live": "When you use a live data connection

SAP Analytics Cloud connects to your remote data source in real time. The data is not replicated

and remains in the source system."

URL: https://help.sap.com/docs/SAPANALYTICSCLOUD/00f68c2e08b941f081002fd3691d86a7/20326321743142478213241952186786.html

3. SAP Learning

Course SACAD1 "SAP Analytics Cloud: Administration and Security": The course materials for the CSAC2501 exam explicitly differentiate between acquired (import) connections

where data is stored in SAC

and live connections

where data remains in the source system. This is a foundational concept covered in the "Data Connectivity" unit.

In SAP Analytics Cloud, both Restricted Measures and Difference From calculations are designed to incorporate dynamic time intelligence. A Restricted Measure allows a user to filter a base measure by one or more dimension members, including dynamic date ranges like "Current Year" or "Year-to-Date". A Difference From calculation is specifically used for time-series comparisons, calculating the variance of a measure against a dynamic, relative time period, such as "Previous Year" or "Previous Quarter". These features enable reports to update automatically based on the current date context.

A. Aggregation: This defines the mathematical operation (e.g., SUM, COUNT) on a set of values. It does not inherently contain dynamic date filtering options; filtering is applied separately.

B. Date Difference: This calculation computes the duration (e.g., number of days or months) between two specific date members, not applying a dynamic time filter to a measure.

1. SAP Help Portal - Restricted Measures: "You can restrict a measure to a fixed or dynamic time range... For dynamic time ranges

you can select Current Date

a specific time range such as Year to Date

or create a custom current date."

Source: SAP Help Portal

"Creating Restricted Measures in a Story". (Specific page content may vary with updates

but the functionality is core to the feature).

2. SAP Help Portal - Difference From Calculation: "The Difference From calculation shows the difference for a measure between a time period and a previous time period... You can select a time offset

such as Previous Year or Previous Period."

Source: SAP Help Portal

"Add a Difference From Calculation". (This documentation details the dynamic time offsets available).