.png)
SAP Analytics Cloud Integration Guide
Integrate SAP Analytics Cloud with enterprise systems through REST, planning, data export, OData-based, and file-oriented services orchestrated by Martini.
SAP Analytics Cloud integration options at a glance
SAP Analytics Cloud integrations primarily use SAP-published REST APIs, including the SAC Resource API, Planning API, and Data Export Service. Planning and export capabilities support bulk or asynchronous data movement for supported models and operations. Selected scenarios also provide OData-based services and file import or export processes. OAuth 2.0 is the recommended approach for unattended API access, with tenant-specific endpoints and role-based permissions configured separately. SAC does not provide a confirmed general-purpose webhook layer or direct SQL access to its tenant database. Martini can schedule workflows, consume these APIs, transform dimensions and measures, validate data, and expose controlled REST APIs for downstream systems.
| Integration point | Supported by SAP Analytics Cloud? | Common use cases | How Martini supports it |
|---|---|---|---|
| REST APIs | Yes | SAP publishes REST resources for supported SAC platform and administrative operations, including resource retrieval and management scenarios. | Martini can consume SAC REST APIs from workflows, apply transformations and business rules, and expose REST APIs around SAC-derived data. |
| Planning APIs | Yes | The SAC Planning API supports planning-data and model-related operations, including selected loads, validations, and planning processes. | Martini can orchestrate planning workflows, validate dimensions and values, submit supported operations, and capture rejected rows or results. |
| Data Export Service | Yes | The Data Export Service extracts data from supported SAC models for warehouses, data lakes, reporting, and reconciliation. | Martini can schedule exports, handle pagination or asynchronous completion, map dimensions and measures, and write results to downstream systems. |
| Bulk, asynchronous, and batch processing | Yes | Planning and data-export capabilities support bulk-oriented data movement, although operation coverage varies by API and model. | Martini workflows can partition large transfers, poll documented asynchronous operations, apply bounded retries, and record batch status. |
| OData-based services | Limited | OData-related services are available in selected SAC model, planning, or external SAP data-source scenarios. | Martini can consume documented OData endpoints when the selected SAC scenario supports them and map the returned structures to target schemas. |
| File import and export | Limited | File-based import and export are available in selected SAC workflows; a universal attachment API was not confirmed. | Martini can process supported CSV or Excel exchanges, validate files, transform rows, and invoke the applicable SAC import or export process. |
| Webhooks and outbound callbacks | Limited | No general-purpose webhook layer covering all SAC content, model, planning, and administrative events was confirmed. Specific feature-level notifications require verification. | Martini can receive a documented callback where available; otherwise it can use scheduled polling, incremental extraction, or an external event source. |
| Authentication | Yes | SAC API access generally uses OAuth 2.0 bearer tokens, tenant-specific endpoints, technical identities, and role-based permissions. | Martini can externalize tenant URLs and OAuth configuration, keep secrets secure, acquire tokens, and call APIs with the required authorization. |
| Database access | No | SAC does not expose direct SQL access to its underlying tenant database for external applications. | Martini can use documented SAC APIs, export services, OData-based services, or the connected source system instead of direct database access. |
How SAP Analytics Cloud exposes data and business events
SAP Analytics Cloud REST APIs
SAP publishes REST APIs for supported SAC platform and administrative resources. Exact resources and operations depend on the tenant, API family, and permissions assigned to the technical identity.
Martini implementation pattern
Martini implementation pattern: a workflow obtains an OAuth access token, calls the tenant-specific SAC endpoint, validates the response, maps the returned resource, and routes the result to a target application, database, or Martini API.
Implementation sequence
SAP Analytics Cloud Planning API
The SAC Planning API is intended for planning-oriented operations, including supported planning data and model-related activities. Availability depends on the model type, tenant configuration, and selected operation.
Martini implementation pattern
Martini implementation pattern: a scheduled or API-triggered workflow retrieves source planning data, validates dimensions and business rules, submits the supported planning operation, and captures completion or rejection details.
Implementation sequence
SAP Analytics Cloud Data Export Service
The Data Export Service provides an API-oriented method for extracting data from supported SAC models for warehouses, data lakes, reporting, and reconciliation processes.
Martini implementation pattern
Martini implementation pattern: a workflow starts or requests an export, handles pagination, partitions, or asynchronous completion, maps SAC dimensions and measures, writes the result downstream, and persists a watermark or batch identifier.
Implementation sequence
SAC file and OData services
Selected SAC scenarios provide OData-based services or file-oriented import and export processes. These capabilities are scenario-specific and should not be treated as a universal interface for every SAC object.
Martini implementation pattern
Martini implementation pattern: a workflow receives or retrieves the supported file or OData payload, validates its structure, converts it to the SAC-specific format, invokes the documented process, and routes validation failures for review.
Implementation sequence
Common SAP Analytics Cloud integration patterns
Pattern 1: Load financial planning data from SAP S/4HANA
When to use this pattern
Use this pattern when approved financial actuals, budgets, or forecasts from SAP S/4HANA must be loaded into an SAC planning model on a scheduled or batch basis.
Integration direction
Example Mapping
| SAP Analytics Cloud Field | Canonical Field | Target Field |
|---|---|---|
| CompanyCode | companyCode | Company dimension member |
| CostCenter | costCenter | Cost Center dimension member |
| FiscalPeriod | fiscalPeriod | Planning period |
| Amount | amount | Measure value |
Martini implementation pattern
A scheduled Martini workflow retrieves approved S/4HANA data, normalizes currencies and fiscal periods, validates company codes, cost centers, accounts, and planning versions, then submits the supported SAC Planning API or import operation. The workflow stores a deterministic batch identifier, captures rejected rows, and retries only transient failures or incomplete asynchronous operations.
Martini capabilities used
- scheduled workflows
- API consumption
- data mapping
- business rules
- validation
- error handling
Pattern 2: Export SAC model data to a data warehouse
When to use this pattern
Use this pattern when analytical or planning model data must be centralized for enterprise reporting, reconciliation, historical storage, or downstream analytics.
Integration direction
Example Mapping
| SAP Analytics Cloud Field | Canonical Field | Target Field |
|---|---|---|
| Dimension member ID | dimensionMemberId | Warehouse dimension key |
| Measure value | measureValue | Fact measure |
| Fiscal period | fiscalPeriod | Period key |
| Model version | modelVersion | Load version |
Martini implementation pattern
Martini invokes the SAC Data Export Service, handles pagination, partitioning, or asynchronous completion, and maps the model output to warehouse tables. It records the model, execution time, batch identifier, watermark, row count, and reconciliation totals so that a failed or partial export can be diagnosed and safely rerun.
Martini capabilities used
- scheduled workflows
- API consumption
- pagination handling
- data mapping
- database integration
- monitoring
Pattern 3: Synchronize workforce planning data from SAP SuccessFactors
When to use this pattern
Use this pattern when workforce, organizational, position, or compensation data from SAP SuccessFactors must be refreshed in an SAC planning model.
Integration direction
Example Mapping
| SAP Analytics Cloud Field | Canonical Field | Target Field |
|---|---|---|
| Employee ID | employeeId | Employee dimension member |
| Organizational unit | organizationalUnit | Organization dimension |
| Position | position | Position dimension |
| Compensation value | compensationValue | Planning measure |
Martini implementation pattern
A Martini workflow retrieves SuccessFactors data, maps organizational structures and workforce attributes, checks inactive members and required planning combinations, and submits accepted rows through the applicable SAC planning or import mechanism. Validation failures are routed to an operations queue or reporting endpoint, while successful batches are reconciled against source counts.
Martini capabilities used
- scheduled workflows
- API consumption
- data transformation
- business rules
- validation
- error routing
Pattern 4: Load Salesforce pipeline data for SAC analysis
When to use this pattern
Use this pattern when Salesforce Accounts, Opportunities, Products, and pipeline measures need to be combined with financial or operational data in SAC.
Integration direction
Example Mapping
| SAP Analytics Cloud Field | Canonical Field | Target Field |
|---|---|---|
| Account ID | accountId | Customer dimension member |
| Opportunity stage | opportunityStage | Pipeline stage |
| Close date | closeDate | Fiscal period |
| Amount | pipelineAmount | Pipeline measure |
Martini implementation pattern
Martini extracts Salesforce data on a schedule or supported incremental basis, standardizes identifiers and dates, applies source-period idempotency controls, validates model members, and loads the transformed dataset into SAC. A reconciliation endpoint or audit store can expose batch status, while bounded retries protect against transient API failures without duplicating accepted loads.
Martini capabilities used
- scheduled workflows
- API consumption
- data mapping
- idempotency
- business rules
- reconciliation
Applications commonly integrated with SAP Analytics Cloud
SAP Analytics Cloud commonly participates in SAP-centered data architectures and can also receive selected data from external business applications. Martini can coordinate these flows, apply canonical mappings, manage authentication, and provide operational controls without treating SAC as a directly accessible database.
| Application | Scenario | Direction | Martini Pattern |
|---|---|---|---|
| SAP S/4HANA | Financial actuals, sales, procurement, inventory, and operational data can support SAC reporting and planning. | SAP S/4HANA → Martini → SAP Analytics Cloud | Schedule a Martini workflow to retrieve approved S/4HANA data, map company codes, cost centers, accounts, periods, currencies, and amounts, validate the planning model requirements, and submit the load through the applicable SAC Planning API or documented import process. |
| SAP BW/4HANA | Governed BW models and enterprise data can provide analytical content for SAC reporting and planning. | SAP BW/4HANA → Martini → SAP Analytics Cloud | Use a scheduled workflow to retrieve or coordinate the supported BW data exchange, transform model-specific dimensions and measures, validate totals, and load or expose the resulting data through the documented SAC integration mechanism. |
| SAP Datasphere | Datasphere can centralize and model data for consumption by SAC analytical content. | SAP Datasphere → Martini → SAP Analytics Cloud | Orchestrate extraction or handoff between Datasphere and SAC, apply schema and period mappings, validate model compatibility, and record batch status and reconciliation results in the workflow. |
| SAP SuccessFactors | Workforce, organizational, and compensation data can support workforce planning and analytics. | SAP SuccessFactors → Martini → SAP Analytics Cloud | Retrieve workforce data, map employees, organizational units, positions, and compensation values to SAC planning dimensions, reject inactive or unmapped members, and submit validated data through the applicable SAC planning or import API. |
| Salesforce | Accounts, opportunities, products, bookings, and pipeline measures can be combined with financial or operational planning data. | Salesforce → Martini → SAP Analytics Cloud | Extract Salesforce objects, normalize identifiers and dates, map pipeline measures to the SAC model, apply source-period idempotency controls, and load the result through a documented SAC data-loading mechanism. |
| ServiceNow | IT spend, service operations, asset, and workforce data can contribute to enterprise analytics. | ServiceNow → Martini → SAP Analytics Cloud | Retrieve selected ServiceNow data through its APIs, transform operational fields into SAC dimensions and measures, validate reporting periods, and load the result through the appropriate SAC API or import process. |
| Microsoft Excel | Excel files are frequently used for planning templates, adjustments, and controlled data exchange. | Microsoft Excel → Martini → SAP Analytics Cloud | Receive or retrieve Excel planning files, validate worksheets and required columns, map rows to SAC dimensions and measures, identify rejected rows, and submit the accepted data through the supported SAC import or planning process. |
| Microsoft Power BI | Organizations may compare or distribute governed analytical data across BI platforms. | SAP Analytics Cloud → Martini → Microsoft Power BI | Extract supported SAC model data, map dimensions and measures to the Power BI ingestion schema, write to the approved downstream endpoint or storage process, and expose reconciliation status through a Martini API if required. |
How to build a SAP Analytics Cloud integration in Martini
Objective
Configure the SAC tenant endpoint, OAuth client, scopes, technical identity, and environment-specific settings without embedding secrets in workflow definitions.
Instructions in Martini
- Create the required SAC OAuth client and permissions
- Store tenant URLs, client identifiers, and secrets in secure Martini configuration
- Use a technical identity with least-privilege access
- Separate development, test, and production configuration
Objective
Select a schedule, API request, or documented feature-level event according to the latency and reliability requirements of the integration.
Instructions in Martini
- Use a Scheduler Trigger for recurring exports or loads
- Use an API trigger when another system initiates the process
- Use a SAC callback only when the selected feature documents one
- Prefer scheduled polling when no suitable SAC event is confirmed
Objective
Call the appropriate SAC REST, Planning API, Data Export Service, OData, or file process and account for pagination or asynchronous completion.
Instructions in Martini
- Acquire an OAuth bearer token
- Call the documented tenant-specific endpoint
- Retrieve every page or partition
- Poll asynchronous operations when required
- Persist batch and watermark information
Objective
Coordinate source retrieval, validation, SAC submission, downstream writes, and operational status as a maintainable Martini workflow.
Instructions in Martini
- Separate extraction, transformation, validation, and load stages
- Use conditional routing for accepted and rejected data
- Store audit information outside transient payloads when appropriate
- Keep source and target batch identifiers correlated
Objective
Convert source fields into SAC Models, Dimensions, Measures, periods, versions, and other model-specific structures.
Instructions in Martini
- Map stable source identifiers to SAC members
- Normalize currencies, units, dates, and fiscal periods
- Transform JSON, OData, or file payloads as required
- Validate required fields and data types before submission
Objective
Protect SAC models from invalid members, duplicate loads, incompatible combinations, and unauthorized data movement.
Instructions in Martini
- Validate dimensions and planning combinations
- Reject inactive or unmapped members
- Apply deterministic idempotency keys
- Reconcile source totals and row counts
- Do not retry authorization or validation failures unchanged
Common SAP Analytics Cloud data objects used in integrations
| Object | Typical Use | Common target systems | Martini handling |
|---|---|---|---|
| Stories | Interactive analytics and dashboard documents containing charts, tables, filters, and visualizations. | Portals, reporting platforms, content repositories, and governance processes | Martini can retrieve or coordinate supported Story resources through the SAC REST API, apply access-aware transformations, and expose controlled downstream APIs where required. |
| Analytic Applications | Scriptable SAC applications that deliver tailored analytical experiences. | Enterprise portals, workflow platforms, and application catalogs | Martini can orchestrate supported resource operations and synchronize metadata or status where the selected SAC API exposes those resources. |
| Models | Analytical or planning structures defining dimensions, measures, attributes, and model data. | Data warehouses, data lakes, financial systems, and planning applications | Martini validates model-specific structures, invokes planning or export services, handles partitions or asynchronous operations, and maps model data to canonical schemas. |
| Dimensions | Master-data structures such as cost centers, products, customers, entities, and organizational units. | SAP S/4HANA, SAP SuccessFactors, SAP Datasphere, warehouses, and planning systems | Martini maps source identifiers to SAC dimension members, validates required members, detects unmapped values, and records rejected rows. |
| Measures | Numeric or calculated values used in analytical and planning models. | Financial systems, CRM platforms, data warehouses, and reporting tools | Martini transforms currencies, units, periods, and numeric formats, applies validation rules, and reconciles source totals with SAC load results. |
| Users and Teams | Security and collaboration objects controlling access to SAC content and data. | Identity providers, HR systems, access-governance platforms, and enterprise directories | Martini can coordinate supported user or team resource operations through the SAC API while preserving SAC roles, permissions, and least-privilege controls. |
Authentication and security considerations
OAuth 2.0 and tenant configuration
SAP Analytics Cloud API integrations generally use OAuth 2.0 bearer tokens. Tenant URLs, API paths, client identifiers, scopes, and secrets should be environment-specific and stored in secure Martini configuration.
Permissions and identities
OAuth authentication does not bypass SAC permissions. Access remains constrained by the technical user, roles, teams, and object-level permissions for Models, Dimensions, planning data, Stories, files, or administrative resources.
Enterprise identity
SAML and SAP Identity Authentication support interactive user sign-on, but they should not be treated as replacements for OAuth credentials used by unattended Martini workflows.
- Use least-privilege technical identities.
- Do not embed secrets or tokens in mappings or scripts.
- Separate development, test, and production SAC tenants.
Operational considerations for SAP Analytics Cloud integrations
Volume and asynchronous processing
Planning and export operations may involve pagination, partitioning, long-running requests, or asynchronous completion. Martini workflows should poll documented operation status and avoid resubmitting an accepted load.
Incremental synchronization
Confirm whether the selected SAC API supports delta extraction. When it does not, use a Martini-managed watermark such as an update timestamp, fiscal period, version, or source batch identifier.
Data quality and model changes
Models, Dimensions, Measures, and planning versions can change. Validate member identifiers, fiscal periods, currencies, data types, and planning combinations before submission.
Retries and reconciliation
- Use bounded exponential backoff for transient failures.
- Do not blindly retry authorization or validation errors.
- Store batch status, row counts, rejected rows, and reconciliation totals.
- Test realistic volumes and representative model changes before production deployment.
Why use Martini instead of scripts or point-to-point integrations?
Orchestrated integration logic
Martini coordinates source extraction, SAC API calls, transformations, validation, business rules, downstream writes, and operational status in reusable workflows rather than scattered scripts.
Maintainable mappings
Mappings for dimensions, measures, currencies, fiscal periods, and planning versions can be maintained as explicit integration logic and adapted when source or SAC models change.
Reliable operations
Martini provides patterns for scheduling, asynchronous processing, error handling, retries, auditing, and environment-specific configuration. This is useful for large exports and planning loads where a point-to-point call is insufficient.
Controlled APIs
Martini can expose REST APIs that give downstream applications controlled access to SAC-derived data or integration status without exposing SAC credentials or implementation details.
Frequently asked questions
SAP Analytics Cloud can integrate through SAP-published REST APIs, the SAC Planning API, Data Export Service, selected OData-based services, and supported file import or export processes. OAuth 2.0 is generally used for unattended API access. Scheduled workflows are appropriate where a general-purpose webhook mechanism is not available.
Yes. Martini can consume SAP Analytics Cloud REST APIs and orchestrate planning, data export, OData-based, and supported file-oriented processes. It can authenticate with OAuth 2.0, transform SAC dimensions and measures, schedule synchronization, and expose controlled REST APIs for downstream systems.
No. A dedicated SAP Analytics Cloud connector is not required. Martini can integrate using SAC's documented REST APIs, Planning API, Data Export Service, supported OData or file mechanisms, and feature-specific event capabilities where confirmed.
Lonti does not charge an additional per-connector or per-vendor fee to integrate SAP Analytics Cloud. The integration is subject to the provisioned capacity of the Martini environment. Separate costs may apply from SAP, cloud infrastructure, or other third-party systems based on subscription, usage, and deployment model.
Use the SAC REST API for supported platform resources, the Planning API for planning-oriented operations, and the Data Export Service for supported model extraction. Selected OData and file processes may be appropriate for specific scenarios. A current SAC GraphQL or SOAP approach was not confirmed.
No general-purpose webhook layer covering every SAC Story, Model, planning, or administrative event was confirmed. Specific feature-level event or callback capabilities should be verified. When no suitable event exists, Martini can use scheduled polling, incremental extraction where supported, or an external SAP event source.
Martini can schedule or expose API-triggered workflows that retrieve SAC data, handle pages or asynchronous operations, map Models, Dimensions, Measures, versions, and periods to canonical schemas, and write to databases or downstream APIs. Watermarks, batch identifiers, and source-period controls can support incremental or repeatable processing.
Martini can distinguish transient HTTP or asynchronous failures from authorization and validation errors, apply bounded retries with backoff, and route rejected rows for review. Deterministic batch identifiers and source keys combined with model, period, or version controls help prevent duplicate planning submissions after timeouts.
Related Martini documentation
Workflows
Integrate SAP Analytics Cloud with Martini
Use Martini to connect SAP Analytics Cloud with enterprise applications, orchestrate planning and export workflows, transform analytical data, and operate integrations with secure, maintainable controls.