SAP Analytics Cloud (SAC) Cheat Sheet

Updated 2026-05-15

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SAP Analytics Cloud (SAC) is SAP's cloud-native SaaS platform for business intelligence, planning, and predictive analytics, combining data visualization, enterprise planning, and augmented analytics in a unified environment. As the strategic analytics solution for the Intelligent Enterprise, SAC connects to SAP BW, S/4HANA, HANA, and third-party sources through live and import connections. The Q1 2026 release introduced Fact Deletion steps, area and Pareto charts, story versioning, and enhanced Compass simulation—critical for maintaining governed, audit-ready planning processes while enabling self-service exploration and AI-driven insights. Understanding the distinction between Stories (presentation-focused dashboards) and Analytic Applications (scripting-enabled interactive apps) is fundamental, as the Classic Experience reaches end-of-life in Q2 2026, making migration to the Optimized Story Experience essential.

What This Cheat Sheet Covers

This topic spans 16 focused tables and 90 indexed concepts, 87 flashcards. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Content Types and Use CasesTable 2: Data Connection TypesTable 3: Model Design and DimensionsTable 4: Planning FeaturesTable 5: Smart Features (AI and Augmented Analytics)Table 6: Visualization and Chart TypesTable 7: Analytics Designer ScriptingTable 8: Administration and SecurityTable 9: Performance OptimizationTable 10: Data Blending and JoiningTable 11: Advanced Planning TechniquesTable 12: Responsive Design and MobileTable 13: Integration and ExtensibilityTable 14: Scheduled OperationsTable 15: Formulas and CalculationsTable 16: Q1 2026 New Features Summary

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Table 1: Content Types and Use Cases

The first decision in any SAC project is which kind of artifact you're building, because each one trades flexibility for effort differently. Stories are the quick presentation-focused dashboards, Analytic Applications open the door to full scripting, planning models add write-back, and supporting pieces like Data Actions, Composites, and Calendar Processes round out the toolkit — knowing when to reach for which saves a lot of rework.

Type	Example	Description
Story	`Create → Story → Add Chart/Table` `Optimized Design Experience`	• Dashboard for data visualization and exploration • supports Responsive and Canvas page layouts, supports limited scripting through button actions and input controls • ideal for executive dashboards and operational reports.
Analytic Application	`Create → Analytic Application` `Analytics Designer scripting`	• Fully scriptable interactive app built with Analytics Designer • enables custom widgets, event-driven logic, data action triggers, and complex navigation flows • ideal for planning user interfaces and scenario analysis tools.
Planning Model	`Create → Model → Planning` `Define Dimensions/Measures`	• Write-enabled data model supporting version management, data actions, and allocation processes • uses Account dimension for financial planning or Measure-based for operational scenarios • supports multi-user collaboration with public/private versions
Data Action	`Create → Data Action` `Add Copy/Allocation/Advanced Formula`	• Automation workflow for planning operations • contains copy steps, allocation steps, Fact Deletion steps (Q1 2026), and advanced formula scripts • orchestrated by Multi Actions for cross-model workflows • supports synchronous and asynchronous execution modes
Data Analyzer	`Open Data Analyzer` `Drag dimensions/measures to table`	• Ad-hoc table-based exploration tool for live SAP BW queries, HANA views, SAC models, and Datasphere • enables drill-down, filters, and calculated measures without creating a story • launched directly or from Explorer mode in charts
Composite	`Create → Composite` `Combine widgets/data/scripts`	• Reusable widget template bundling layout, data bindings, styling, and scripting • enables standardized KPI tiles, reusable chart templates, and consistent brand styling • supports data source remapping when applied to new models
Value Driver Tree (VDT)	`Add VDT widget to story` `Define driver nodes and formulas`	• Hierarchical KPI visualization for scenario analysis • links driver measures (e.g., price, volume) to outcome measures (e.g., revenue) • enables what-if simulations by adjusting sliders • displays formula relationships between nodes for transparent logic.
Calendar Process	`Calendar → Create Process Template` `Define tasks/approvals/due dates`	• Workflow orchestration for multi-stage planning cycles • defines tasks, assignments, due dates, and approval chains • supports notifications, status tracking, and process monitoring • integrates with calendar views for visibility

Table 2: Data Connection Types

The single most consequential architectural choice in SAC is live versus import — does the data stay in the source system and get queried in real time, or get copied into the SAC tenant where you can wrangle it offline? Each connection type below lands somewhere on that spectrum, with the on-premise tunnel, OData write-back, and the new Snowflake live link covering the trickier integration scenarios.

Connection	Example	Description
Live Data Connection	`Connections → Add → Live` `SAP BW, HANA, S/4HANA`	• Real-time query against source system • data stays in backend • no data replication • supports SAP BW (BICS), HANA (MDX), S/4HANA, Datasphere • requires CORS for browser-based or Cloud Connector for on-premise • supports BW variables and HANA input parameters.

The rest of this section is part of the full cheat sheet

Table 3: Model Design and Dimensions

A model is only as good as the dimensions and measures underneath it, and SAC has a few specialized ones worth understanding early. The Account dimension drives financial planning, the Version dimension separates actuals from budget and forecast, and the calculated dimension/measure rows show what you can build at the story level without touching the model itself.

Concept	Example and usage	Description
Generic Dimension	`Add Dimension → Generic` `e.g., Product, Customer, Region`	• Categorical master data with hierarchy support • each member has ID and Description • supports parent-child hierarchies, level-based hierarchies, and properties (attributes) • used for drill-down and filtering.

The rest of this section is part of the full cheat sheet

Table 4: Planning Features

Planning is what separates SAC from a pure BI tool — users don't just read data, they write it back and run it through automated workflows. These rows are the planning engine: public and private version sandboxes, allocation and copy logic, the Data Action steps (including the Q1 2026 Fact Deletion step) that orchestrate it, and the predictive and simulation features that look forward instead of back.

Feature	Example	Description
Public vs. Private Versions	`Public: Budget_2026` `Private: MyScenario (auto-copy)`	• Public versions are shared across users • Private versions are user-specific sandboxes for what-if analysis • private changes can be published to public after approval • enables collaborative planning with personal workspace.

The rest of this section is part of the full cheat sheet

Table 1: Content Types and Use Cases

Type	Example	Description
Story	`Create → Story → Add Chart/Table` `Optimized Design Experience`	• Dashboard for data visualization and exploration • supports Responsive and Canvas page layouts, supports limited scripting through button actions and input controls • ideal for executive dashboards and operational reports.
Analytic Application	`Create → Analytic Application` `Analytics Designer scripting`	• Fully scriptable interactive app built with Analytics Designer • enables custom widgets, event-driven logic, data action triggers, and complex navigation flows • ideal for planning user interfaces and scenario analysis tools.
Planning Model	`Create → Model → Planning` `Define Dimensions/Measures`	• Write-enabled data model supporting version management, data actions, and allocation processes • uses Account dimension for financial planning or Measure-based for operational scenarios • supports multi-user collaboration with public/private versions
Data Action	`Create → Data Action` `Add Copy/Allocation/Advanced Formula`	• Automation workflow for planning operations • contains copy steps, allocation steps, Fact Deletion steps (Q1 2026), and advanced formula scripts • orchestrated by Multi Actions for cross-model workflows • supports synchronous and asynchronous execution modes
Data Analyzer	`Open Data Analyzer` `Drag dimensions/measures to table`	• Ad-hoc table-based exploration tool for live SAP BW queries, HANA views, SAC models, and Datasphere • enables drill-down, filters, and calculated measures without creating a story • launched directly or from Explorer mode in charts
Composite	`Create → Composite` `Combine widgets/data/scripts`	• Reusable widget template bundling layout, data bindings, styling, and scripting • enables standardized KPI tiles, reusable chart templates, and consistent brand styling • supports data source remapping when applied to new models
Value Driver Tree (VDT)	`Add VDT widget to story` `Define driver nodes and formulas`	• Hierarchical KPI visualization for scenario analysis • links driver measures (e.g., price, volume) to outcome measures (e.g., revenue) • enables what-if simulations by adjusting sliders • displays formula relationships between nodes for transparent logic.
Calendar Process	`Calendar → Create Process Template` `Define tasks/approvals/due dates`	• Workflow orchestration for multi-stage planning cycles • defines tasks, assignments, due dates, and approval chains • supports notifications, status tracking, and process monitoring • integrates with calendar views for visibility

Table 2: Data Connection Types

Connection	Example	Description
Live Data Connection	`Connections → Add → Live` `SAP BW, HANA, S/4HANA`	• Real-time query against source system • data stays in backend • no data replication • supports SAP BW (BICS), HANA (MDX), S/4HANA, Datasphere • requires CORS for browser-based or Cloud Connector for on-premise • supports BW variables and HANA input parameters.

Table 3: Model Design and Dimensions

Concept	Example and usage	Description
Generic Dimension	`Add Dimension → Generic` `e.g., Product, Customer, Region`	• Categorical master data with hierarchy support • each member has ID and Description • supports parent-child hierarchies, level-based hierarchies, and properties (attributes) • used for drill-down and filtering.

Table 4: Planning Features

Feature	Example	Description
Public vs. Private Versions	`Public: Budget_2026` `Private: MyScenario (auto-copy)`	• Public versions are shared across users • Private versions are user-specific sandboxes for what-if analysis • private changes can be published to public after approval • enables collaborative planning with personal workspace.