Live Data Connection

In a Live connection, data never leaves the source system. SAC only retrieves metadata (to build the model) and queries the source system in real-time when a user opens a story. The heavy lifting (aggregations, calculations) is done by the source database.

• Data Privacy: Highly secure; sensitive data remains behind your corporate firewall.
• Freshness: Real-time. What you see is exactly what is in the source at that second.
• Authorization: Security roles defined in the source system (e.g., SAP BW Analysis Authorizations or HANA privileges) are strictly applied.
• Supported Sources: SAP HANA, SAP BW/4HANA, SAP S/4HANA, SAP Datasphere, SAP BPC, SAP Universe (BOBJ).

Acquired (Import) Data Connection

In an Import connection, data is physical copied (extracted) from the source system and stored securely inside SAC's internal HANA database. Data can be refreshed via scheduled jobs.

• Data Blending: Allows joining data from multiple disparate sources (e.g., SAP S/4HANA + Salesforce + flat files) inside the SAC model.
• Smart Features: Full access to Smart Predict and advanced wrangling features.
• Planning: Requires imported models (except when planning against SAP BPC live or specific Datasphere architectures).
• Supported Sources: Almost anything (OData, SQL databases, SuccessFactors, Concur, Google Drive, Excel, flat files).

Comparison Matrix

SAP Cloud Connector & SAC Agent

To connect to on-premise systems (both Live and Import), you must install the SAP Cloud Connector. For Import connections specifically from on-premise sources (like SQL Server or older SAP ERP), the SAP Analytics Cloud Agent is also required to facilitate data extraction.

License Types

Licenses represent the commercial entitlement. A user must be assigned a license type before they can do anything. The primary licenses are:

Standard Roles

While licenses grant the capability, Roles grant the actual permission to execute actions. SAC comes with standard roles, and administrators can create custom roles.

• Admin: Full access to system configuration, security, and all objects.
• Modeller: Create and maintain connections, dimensions, and models.
• Viewer: Read-only access to stories and dashboards.
• Planner: Can input data into planning models and publish versions.

Datasets vs Models

Before diving into models, it's important to understand datasets:

• Dataset: A flat, unstructured table of data. Excellent for quick, ad-hoc data exploration and Smart Predict. Less rigid.
• Model: A structured star-schema. Enforces data governance, hierarchies, and planning logic. Essential for enterprise reporting and planning.

The Classic Model (Account-Based)

Historically, SAC utilized an Account-based model. In this architecture, all numeric data is stored in a single generic measure column, and an "Account" dimension dictates what that number means (e.g., Revenue, Cost, Quantity).

• Rigid structure: Always requires an Account dimension.
• Familiar to SAP BPC and Finance users.
• Currency conversion and aggregations are defined on the Account members.

The New Model (Measure-Based)

Introduced to align with modern data warehousing (like SAP Datasphere and Snowflake), the New Model allows for multiple explicit measure columns (e.g., one column for Revenue, one for Quantity, one for Discount).

New Model Features

Dimension Types

SAC enforces specific dimension types to ensure data behaves correctly, especially for time-series charts and planning.

Hierarchies

Hierarchies allow users to drill down from high-level summaries to granular details. SAC supports two main types:

• Level-based Hierarchies: Defined by columns (e.g., Country Column > State Column > City Column).
• Parent-Child Hierarchies: Defined by relationships within members of a single dimension (e.g., Employee ID and Manager ID). Best for unbalanced organizational charts.

Public vs Private Dimensions

Transformations

SAC provides an Excel-like grid interface for data wrangling. Common operations include:

• Concatenate / Split: Combine First Name and Last Name, or split a composite string.
• Replace / Fill: Replace null values with a default string (e.g., "Unassigned").
• Change Data Type: Convert a string representation of a date into an actual Date format SAC can recognize.

Custom Expressions

For advanced transformations, SAC uses a formula language similar to Excel. You can create custom columns based on logic:

-- Example: Creating a Region column based on Country
IF([Country] = 'US' OR [Country] = 'CA', 'North America', 'Other')

Mapping to the Model

During the data import process, you map the columns from your flat file or SQL query to the Dimensions and Measures defined in your SAC Model. If a member exists in your incoming data that doesn't exist in a Public Dimension, you can configure the job to either reject the row or auto-create the new master data member.

Optimized Story Experience (ODE)

Historically, SAC had separate interfaces for "Stories" (BI) and "Analytic Applications" (advanced scripting). The Optimized Story Experience unifies these. ODE offers faster loading times, smoother interactions, and the ability to seamlessly transition from a standard dashboard to a highly customized scripted application.

Page Types

Story Structure & Theming

Good story design utilizes Themes (to consistently apply corporate colors and fonts across all charts) and Templates (to ensure standardized layouts across departments).

Chart Types

Advanced Table Features

Tables in SAC are incredibly powerful, acting as more than just data grids:

• In-Cell Charts: Display micro-bar charts directly inside table cells to visualize magnitudes instantly.
• Thresholds: Apply conditional formatting (red, yellow, green) based on rules or target comparisons.
• Responsive Styling: Tables can auto-hide columns on smaller screens while preserving key data.

Variances

Instead of manually calculating differences, SAC allows you to add Variances directly to charts. You can instantly show the difference between Actuals vs. Budget (both absolute value and percentage) integrated visually into a bar chart.

Filter Scope

Filters can be applied at different levels of the story hierarchy:

Linked Analysis

Linked Analysis allows widgets to interact with each other. If you click on "North America" in a pie chart, you can configure it so that a bar chart next to it automatically filters to show only North American sales.

Input Controls

Input controls are UI elements (like dropdowns, sliders, or radio buttons) placed directly on the canvas. They allow users to easily toggle filters or swap measures/dimensions dynamically without opening complex menus.

When to use Scripting

While SAC's drag-and-drop interface is powerful, scripting is necessary when you need:

• Custom Workflows: Guiding a user through a multi-step planning process with "Next" and "Back" buttons.
• Dynamic UI Changes: Hiding/showing charts, changing colors, or swapping data sources based on a specific button click or variable state.
• Custom API Calls: Sending data to external systems or triggering BTP integration flows via REST APIs.

Scripting Environment

Scripts are attached to Events. For example, a Button widget has an onClick event. A Dropdown has an onSelect event. You write code that executes when that event fires.

-- Example: Changing a chart dimension via a dropdown selection
var selection = Dropdown_1.getSelectedKey();
Chart_1.removeDimension("Product", Feed.CategoryAxis);
Chart_1.addDimension(selection, Feed.CategoryAxis);

Custom Widgets

If SAC's standard chart library doesn't meet a specific need (e.g., a highly specific network diagram or D3.js visualization), developers can create Custom Web Components and import them into SAC to be used alongside standard charts.

Versions (Public vs Private)

Version management is central to SAC Planning. Versions allow multiple "truths" to exist simultaneously without overwriting Actuals.

Data Locking & Validation

To control the planning cycle, administrators use Data Locking. You can lock specific slices of data (e.g., locking Q1 Actuals so they cannot be changed, while leaving Q2-Q4 Open for forecasting).

Validation Rules ensure data integrity (e.g., preventing users from planning Headcount expenses against a non-HR cost center).

Calendar & Tasks

The SAC Calendar is a workflow orchestration tool. Managers can create Tasks (e.g., "Complete Regional Q3 Budget"), assign them to specific planners, set deadlines, and track the progress of the entire planning cycle.

What is a Data Action?

A Data Action is triggered by the end-user via a button in the story. It acts as a batch processor. Common uses include:

• Copying Actuals from last year into the Budget version for next year.
• Calculating depreciation across hundreds of assets.
• Applying a blanket 5% inflation increase to all operational expenses.

Data Action Steps

A single Data Action can contain multiple sequential steps:

Advanced Formula Scripting

Advanced Formulas allow you to execute logic that cannot be achieved with simple visual rules.

-- Example: Increase next year's budget by a parameter variable
DATA([d/Version]="Budget", [d/Date]="2025") = 
  RESULTLOOKUP([d/Version]="Actuals", [d/Date]="2024") * @InflationRate

The Allocation Process

A typical scenario: The IT department has a total cost of $1,000,000 stored at a generic "Corporate" level. This cost needs to be allocated to the Sales, Marketing, and HR departments based on their respective headcount.

Visual Allocation Rules

SAC provides a visual designer to build these steps without scripting. You create an Allocation Process containing multiple Allocation Steps. These processes can be attached to a Data Action button so end-users can run them on demand after inputting driver data.

What is a VDT?

A VDT links various business drivers mathematically in a visual flowchart. For example, a tree might show: Gross Margin = Revenue - Cost of Goods Sold. Where Revenue = Volume * Price.

Nodes in the tree represent measures and dimensions from your planning model.

Simulation & What-If Analysis

The primary use case for a VDT is rapid simulation. In an SAC Story, a user can interact with the VDT directly:

• Change the "Price" node by +5%.
• The VDT instantly calculates the ripple effect through the tree, updating Revenue and ultimately Gross Margin.
• This creates a Private Version, allowing the user to simulate multiple "what-if" scenarios (e.g., Best Case vs. Worst Case) before finalizing the plan.

Smart Predict

Smart Predict creates dedicated predictive scenarios. It automatically tests multiple ML algorithms behind the scenes and selects the most accurate one for your dataset.

Smart Insights

Smart Insights works directly within a story. By clicking the "lightbulb" icon on a data point (e.g., a dip in Q2 Revenue), SAC analyzes the underlying data and generates natural language explanations and charts highlighting the top contributors to that value (e.g., "Revenue is down because Product X sales dropped 40% in Germany").

Smart Discovery

Smart Discovery automates dashboard creation. You select a target measure (e.g., Profit), and SAC runs a machine learning algorithm against the entire model to discover key influencers, outliers, and patterns. It then automatically generates a multi-page story visualizing these findings.

Folder & Object Level Security

Stories, Models, and files are organized into Folders. Access rights (View, Edit, Delete, Share) are applied to these folders. Users or Teams are granted access to the folders, inheriting the permissions for the objects inside.

Teams

Instead of assigning roles and folder access to individual users, best practice is to use Teams (e.g., "Finance Planners US"). When a new employee joins, you simply add them to the Team, and they inherit all necessary roles and folder access.

Data Access Control (DAC)

While folder security controls access to the Story, Data Access Control restricts access to the rows of data within the model.

• Enabled at the Dimension level (e.g., turning on DAC for the 'Region' dimension).
• You map users or teams to specific dimension members (e.g., User A can only see data where Region = 'North America').
• When User A opens a story, the data is automatically filtered to their authorized regions.

Content Network

The Content Network is SAC's internal mechanism for transporting objects.

SAP Business Content

The Content Network is also where customers can download SAP Standard Business Content. These are free, pre-built packages created by SAP for specific industries (e.g., Retail, Banking) or Lines of Business (e.g., HR, Finance, S/4HANA integrations). They provide best-practice models, stories, and data actions out-of-the-box, significantly accelerating implementation time.

Most Asked Comparison Questions

Live vs Import Connection

Classic Model vs New Model

Story Filters vs Page Filters vs Input Controls

Key Terms to Know Cold

Common Interview Questions

1. What are the primary differences between a Live and an Import connection? When would you use each?
2. Explain the difference between an Account-based (Classic) model and a Measure-based (New) model.
3. How does SAC handle data security at both the object (folder) level and the data row level?
4. Walk me through the steps to set up a basic allocation process in SAC Planning.
5. What is a Data Action, and what are the different types of steps you can include in one?
6. How does Smart Predict differ from Smart Insights?
7. What is the difference between a Responsive page and a Canvas page in an SAC Story?
8. How do you transport content from a Development SAC tenant to a Production tenant?