SAP Business Technology Platform (SAP BTP) is SAP’s unified platform for building, integrating and extending enterprise applications. Within SAP BTP, the Analytics track is where organizations turn operational data into decisions - with trusted reporting, interactive dashboards, planning workflows and predictive insights. At the center of this track sits SAP Analytics Cloud (SAC), a single cloud solution that brings BI (Business Intelligence), Planning and Predictive analytics together in one experience.
This article by Multisoft Systems explains how SAC fits into the SAP BTP Analytics track online training and how teams use it to deliver end-to-end analytics - from data connection and modeling to storytelling, planning cycles and predictive outcomes.
Where SAP Analytics Cloud fits in the SAP BTP Analytics track?
The SAP BTP Analytics track is not just “a reporting tool.” It is an ecosystem of capabilities that help enterprises:
- Connect to SAP and non-SAP data sources
- Govern data and definitions across teams
- Enable self-service analytics without losing control
- Build enterprise-grade planning and forecasting processes
- Use augmented analytics and predictive models to move from hindsight to foresight
SAP Analytics Cloud supports these goals by combining three pillars:
- BI - dashboards, stories, visual exploration, enterprise reporting
- Planning - budgets, forecasts, allocations, workflows, version management
- Predict - forecasting, classification, regression, driver analysis, smart insights
Because it is part of SAP’s analytics portfolio, SAC also integrates strongly with other SAP analytics services and data platforms such as SAP S/4HANA, SAP BW or BW/4HANA, SAP Datasphere and SAP HANA.
SAP Analytics Cloud overview: one interface, multiple outcomes
SAP Analytics Cloud (SAC) is SAP’s cloud-based analytics solution that brings Business Intelligence (BI), planning and predictive capabilities into one unified interface. Instead of using separate tools for dashboards, budgeting, forecasting and advanced analytics, SAC provides a single workspace where users can explore data, build interactive stories and turn insights into action. This “one interface, multiple outcomes” approach helps organizations reduce silos between reporting and planning teams, standardize metrics across departments and accelerate decision-making. SAC connects to SAP and non-SAP data sources through both live connections (real-time querying from the source system) and import connections (data acquisition into SAC for enrichment, blending and performance optimization), allowing businesses to choose the right approach based on governance, speed and flexibility needs. Within the same environment, analysts can model data by defining measures, dimensions, hierarchies and calculations to ensure consistent reporting, while business users can consume content through intuitive dashboards, tables and visualizations with filters, drill-downs and smart insights.
SAC also supports enterprise planning with versions (actual, budget, forecast), input-ready forms, workflows, approvals and automation features such as data actions and multi-actions, enabling structured and auditable planning cycles. For predictive outcomes, SAC offers augmented analytics and Smart Predict capabilities to generate forecasts, identify key drivers and highlight patterns that may impact future performance - all without forcing users to switch platforms. Collaboration is built into the experience through commenting, sharing, task assignments and calendar-based planning activities, making SAC not just a reporting layer but a decision and performance management hub. With role-based security and governance controls, organizations can scale SAP BTP training across business units while keeping data access controlled and content consistent, ultimately delivering faster insights, more connected planning and smarter forecasts from a single, modern analytics interface.
BI in SAP Analytics Cloud: from reporting to interactive storytelling
1) Data connectivity for BI: live vs import
In SAP Analytics Cloud (SAC), BI starts with the right connectivity choice - live or import. Live connections query data directly from the source in real time, helping teams keep a single source of truth and avoid replication while supporting up-to-date reporting. Import connections pull data into SAC, enabling enrichment, blending, transformations and scheduled refresh for flexible analysis and strong performance. Live is ideal for governed, real-time insights with minimal duplication, while import suits scenarios needing data mashups, offline modeling, and custom calculations. Many enterprises use a hybrid approach based on security, speed and business needs.
2) Modeling for BI: semantic consistency and reusability
SAC modeling creates a consistent semantic layer so every dashboard and report speaks the same business language. Models define measures, dimensions, hierarchies, time structures and calculations, ensuring that key metrics like revenue, margin, headcount or cost are computed uniformly across teams. This reduces conflicting numbers between departments and improves trust in analytics. Reusable models also accelerate development - once a model is built, multiple stories and applications can consume it without rebuilding logic. With controlled master data, mapping and calculated measures, SAC modeling supports scalable self-service analytics while maintaining enterprise-level consistency.
3) Stories: dashboards that answer business questions
SAC Stories move BI from static reporting to interactive storytelling by combining charts, tables, KPIs and filters into guided analytical narratives. Users can drill down, slice by dimensions, compare periods and explore variances without leaving the dashboard. The best stories are built around business questions - such as “Why did sales drop?” or “Which region drives profitability?” - rather than simply visualizing raw data. Smart insights and contextual interactions help users identify drivers faster, while input controls and linked analysis create a seamless exploration flow. Stories enable both executive summaries and deep dives in one experience.
4) Enterprise reporting: formatted, repeatable outputs
Enterprise reporting in SAC focuses on delivering structured, formatted and repeatable outputs that finance, compliance and leadership teams can rely on. Beyond interactive dashboards, organizations often need standardized statements, management packs and regulatory-style reports with consistent layouts, totals and hierarchies. SAC supports table-centric reporting, controlled formatting and reusable templates so reporting cycles become faster and less manual. When combined with scheduling and governed distribution (based on setup), reports can be refreshed regularly and shared consistently across stakeholders. This reduces dependency on spreadsheet-based packs and helps ensure that recurring reports remain accurate, traceable and easy to reproduce.
5) Governance for BI: roles, content management and lifecycle
Strong governance in SAC ensures BI remains scalable, secure and consistent as adoption grows. Role-based access controls define what users can view, edit or administer across connections, models, stories and folders. Content management practices - such as structured workspaces, naming conventions and controlled sharing - prevent dashboard sprawl and reduce duplication. Lifecycle management supports moving content from development to test to production in a controlled way, minimizing risk to business reporting. Administrative monitoring and audit-friendly controls help track usage and changes. Effective governance enables self-service analytics without compromising data security, standard definitions or enterprise reporting reliability.
Planning in SAP Analytics Cloud: connected planning on a single platform
- Unified BI + Planning in one interface
- Integrated planning models (accounts, entity, cost center, product, time)
- Version management (Actual, Budget, Forecast, What-if)
- Driver-based planning (rates, volumes, price, headcount)
- Input forms with validations and guided entry
- Top-down, bottom-up planning with rollups
- Allocations, distributions and spreading logic
- Data Actions for automated calculations and mass updates
- Multi-Actions to run chained planning steps in sequence
- Planning workflows (tasks, reviews, approvals, status tracking)
- Calendar-based planning cycles and deadlines
- Collaboration: comments, discussions, ownership by org unit
- Forecasting support with scenario comparison
- Variance analysis (Plan vs Actual vs Forecast) within the same story
- Security and data access control by organization/hierarchy
- Auditability with controlled changes and governance
- Currency and unit handling for global planning (as configured)
- Integration with SAP data platforms for actuals and master data
- Predictive planning use cases (baseline forecast + planner adjustments)
Predict in SAP Analytics Cloud: turning patterns into foresight
Predict in SAP Analytics Cloud (SAC) helps organizations move beyond historical reporting by identifying patterns and converting them into forward-looking insights. Using augmented analytics and Smart Predict capabilities, SAC can generate forecasts, detect key drivers behind performance changes and highlight trends that may impact future outcomes. Business users can explore predictive results directly within the same environment used for dashboards and planning, reducing tool switching and speeding up decisions. Predict features support common scenarios like demand forecasting, sales trend projections, risk classification and driver-based impact analysis, enabling teams to test assumptions and compare scenarios. When combined with SAC Planning, predictive outputs can create baseline forecasts that planners refine, improving accuracy and agility across planning cycles.
Skills covered in the SAP BTP Analytics track with SAC
Skills covered in the SAP BTP Analytics track with SAP Analytics Cloud (SAC) certification span technical, functional and governance-focused capabilities needed to deliver trusted enterprise analytics. Professionals typically learn how to navigate SAC, design user-friendly stories and apply dashboard best practices, including filters, input controls, drill-downs and performance optimization. Strong emphasis is placed on data connectivity decisions - understanding live versus import connections, setting up secure connections, scheduling refresh and handling data blending where required. Modeling skills include building reusable SAC models, managing measures and dimensions, creating hierarchies and time structures, defining calculated and restricted measures, and maintaining semantic consistency so KPIs remain standardized across teams. In enterprise BI, learners develop skills in formatted reporting, table design, variance analysis and distributing repeatable outputs for stakeholders. Planning-focused skills cover building planning models and versions (Actual, Budget, Forecast, What-if), creating driver-based planning logic, designing input-ready forms, implementing workflows, approvals and calendar-based planning cycles, plus automating calculations through data actions and multi-actions. Predictive and augmented analytics skills include using Smart Predict for forecasting, regression and classification use cases, interpreting driver influence, and embedding predictive insights into stories and planning processes. Governance and administration skills are also essential, such as role-based security, data access control, content organization, lifecycle management and monitoring adoption and usage. Together, these skills prepare learners to work as SAC analysts, BI developers, planning consultants, analytics architects and business-facing analytics leads on SAP BTP.
Conclusion
The SAP BTP Analytics track is designed to help organizations move from fragmented reporting and spreadsheet-based planning to a modern analytics operating model. SAP Analytics Cloud enables that shift by combining BI, Planning and Predict in one platform - so teams can analyze what happened, plan what should happen and anticipate what is likely to happen next.
When implemented with strong modeling, governance and process ownership, SAC becomes a strategic layer that connects business questions to trusted data and turns insights into action at scale. Enroll in Multisoft Systems now!