Learn the core concepts of SAP Analytics Cloud (SAC), including business intelligence, planning, predictive analytics, and data visualization.

Develop expertise in creating real-time dashboards, stories, visualizations, and executive reports for business decision-making.

Gain hands-on experience connecting SAP and non-SAP data sources, modeling datasets, and performing advanced analytics.

Acquire practical skills required for SAP Analytics Cloud implementation, reporting, planning, forecasting, and analytics consulting roles.

SAP Analytics Cloud (SAC) is a cloud-based analytics platform that combines business intelligence, augmented analytics, predictive analytics, and enterprise planning. It allows organizations to analyze data, create visualizations, build plans, and generate business insights in one environment.

The major SAC capabilities include business intelligence, data visualization, data modeling, enterprise planning, predictive analytics, reporting, collaboration, and administration. These capabilities support both analytical and planning use cases.

SAC can be used to create dashboards, interactive stories, analytical reports, planning models, forecasts, KPI reports, and predictive scenarios. It can work with SAP and supported non-SAP data sources for enterprise analytics.

A story is an analytical document that can contain charts, tables, visualizations, filters, text, and other objects. Stories are used to present and analyze business data interactively.

Dimensions represent descriptive business information such as customer, product, region, or time. Measures represent numerical values such as revenue, cost, quantity, and profit that can be analyzed using dimensions.

Data modeling defines how business data is structured for analytics or planning. A model can contain dimensions, measures, hierarchies, calculations, attributes, and other components required for analytical processing.

Calculated measures are metrics created using formulas based on existing measures or data elements. They can be used for calculations such as profit margins, percentages, growth rates, and variances.

Restricted measures are measures filtered to specific dimension members or conditions. For example, a restricted measure can represent sales for a particular region, product category, or reporting period.

Hierarchies organize dimension members into logical levels. They allow users to analyze data from summarized levels down to more detailed business information.

A live connection provides access to data directly from the source system, while an import connection brings supported data into SAC. The appropriate approach depends on data architecture, security, performance, and business requirements.

A live connection allows SAC to work with data directly from a supported source system without replicating the underlying data into SAC. This can be useful when organizations require access to current source-system data or have data-security requirements.

An import connection transfers supported source data into SAC. The imported data can then be used for models, stories, dashboards, analysis, and other supported SAC scenarios.

Yes. SAP Analytics Cloud supports integration scenarios with SAP S/4HANA for analytics and planning. Supported connection approaches can allow SAC to consume or exchange business data with S/4HANA.

SAP HANA can provide data to SAC through supported connectivity options. HANA-based data can be used for analytical models, stories, dashboards, and business reporting.

SAP BW and BW/4HANA can provide governed enterprise data for SAC analytics. SAC can use supported connections to build reporting and visualization solutions on top of SAP data.

SAP Datasphere can act as a governed data foundation for analytical scenarios. SAC can consume modeled data from Datasphere to create stories, dashboards, reports, and other analytical content.

OData connections allow SAC to consume data exposed through supported OData services. They can be used for integration with compatible SAP and external applications.

REST API connectivity can be used in supported integration scenarios to exchange or access data through web-based services. Authentication and connection configuration depend on the specific service and SAC integration method.

Analytic models provide a structured foundation for analyzing business data. They can contain dimensions, measures, calculations, and other data structures required for reporting and analysis.

A planning model is designed for business planning activities such as budgeting, forecasting, and scenario planning. Planning models provide planning-specific capabilities such as versions, data entry, auditing, and security.

SAC Planning provides functionality for creating, maintaining, analyzing, and sharing business plans. It supports activities such as budgeting, forecasting, version management, data entry, and other planning processes.

Version management allows users to work with different versions of planning data. Common planning scenarios include actual, budget, forecast, and simulation versions.

Data locking restricts changes to selected planning data according to defined rules. It can help protect finalized or approved planning values from unintended modifications.

Data actions are structured operations that can automate data-processing activities in planning models. They can support calculations, copying data, allocations, and other planning operations.

Multi-actions combine multiple supported planning or data-processing operations into a single sequence. They can help automate complex planning workflows and reduce repetitive manual activities.

Allocations distribute values across selected planning dimensions based on defined rules. They can be used for distributing costs, budgets, revenue, or other planning values.

Forecasting uses historical and business data to estimate future values or trends. SAC can support forecasting scenarios for areas such as sales, finance, demand, and operational planning.

Predictive analytics uses statistical and machine-learning capabilities to identify patterns and generate predictions from historical data. SAC provides predictive capabilities for supported analytical and planning scenarios.

Predictive planning combines predictive forecasting capabilities with planning processes. It can help organizations incorporate forecast information into planning and decision-making workflows.

Smart Insight helps users investigate the factors contributing to a selected data point or variance. It provides additional analytical context to help users understand underlying data relationships.

Smart Discovery uses automated analytical techniques to explore data and identify patterns, relationships, and potential insights. It helps users investigate business information without manually building every analytical view.

Filters restrict the data displayed in an analytical view according to selected conditions. Input controls allow users to interactively select dimension members or values that influence the displayed analysis.

Linked analysis allows selections made in one visualization to affect other related visualizations. It is useful for interactive dashboard analysis where multiple charts need to respond to user selections.

Charts provide graphical representations of business data, while tables provide detailed multidimensional views. Together, they can be used to build interactive dashboards and analytical reports.

Yes. SAC stories can support additional custom chart types when they are available or installed for the relevant tenant. Custom charts can provide additional visualization options beyond standard chart types.

Geo maps display business information based on geographical locations. They can be used to analyze metrics such as sales, customers, operations, or performance across regions and territories.

An analytic application is an interactive analytical solution containing components such as charts, tables, filters, and other interface elements. It can provide customized interactions for specific analytical use cases.

Analytics Designer provides development capabilities for building customized analytical applications. It can be used when organizations require more controlled interactions and application-specific analytical workflows.

A SAC tenant is an environment in which the organization's SAC content, users, models, connections, and configurations are maintained. Tenant administration involves managing system settings, access, content, and integrations.

SAC security uses roles, permissions, teams, data-access controls, and related security mechanisms to control what users can access and perform. Access can be configured according to organizational and business requirements.

Row-level or data-level security restricts access to particular records or dimension members based on configured access rules. It allows different users or groups to work with only the business data they are authorized to view.

Single Sign-On allows users to authenticate through a supported identity provider rather than maintaining separate credentials for each application. SAC supports supported identity and authentication configurations for enterprise environments.

SAC can be integrated with supported SAP S/4HANA scenarios for analytics and planning. Depending on the architecture, supported OData and other connectivity mechanisms can be used to exchange or consume relevant business data.

SAC can combine KPIs, charts, tables, filters, and other visualizations into interactive analytical content. This allows organizations to present business performance information through dashboards designed around specific management and reporting requirements.

Enterprise reporting involves delivering standardized business information across departments and organizational functions. SAC can be used to build reporting solutions for areas such as finance, sales, HR, operations, and management.

Yes. SAC planning capabilities can support budgeting, forecasting, scenario analysis, and financial planning processes. Planning models provide features designed specifically for business planning activities.

SAC can combine sales measures and dimensions into interactive dashboards and analytical stories. Sales teams can analyze metrics such as revenue, volume, regional performance, customer trends, and forecasts based on the available data model.

SAC can be used to analyze workforce-related metrics through dashboards, stories, planning models, and analytical content. Depending on the available data, organizations can analyze workforce trends, staffing metrics, performance indicators, and planning scenarios.

Basic knowledge of business intelligence, data analysis, databases, and reporting is useful for learning SAC. Advanced technical work can benefit from knowledge of data modeling, SQL, APIs, SAP HANA, SAP S/4HANA, SAP BW, and SAP Datasphere.

You can develop skills in SAC navigation, data connectivity, live and import connections, data modeling, story development, dashboard design, visualization, planning, budgeting, forecasting, predictive analytics, SAP integration, security, and enterprise reporting. The Chennai course page also includes practical work involving executive dashboards, sales analytics, financial planning, workforce analytics, and SAP integration projects.