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name: sap-datasphere description: | Comprehensive plugin for SAP Datasphere development with 3 specialized agents, 4 slash commands, and validation hooks. Use when building data warehouses on SAP BTP, creating analytic models, configuring data flows and replication flows, setting up connections to SAP and third-party systems, managing spaces and users, implementing data access controls, using the datasphere CLI, creating data products for the marketplace, or monitoring data integration tasks. Covers Data Builder (graphical/SQL views, local/remote tables, transformation flows), Business Builder (business entities, consumption models), analytic models (dimensions, measures, hierarchies), 40+ connection types (SAP S/4HANA, BW/4HANA, HANA Cloud, AWS, Azure, GCP, Kafka, Generic HTTP), real-time replication, task chains, content transport, CLI automation, catalog governance, and data marketplace. Includes 2025 features: Generic HTTP connections, REST API tasks in task chains, SAP Business Data Cloud integration. Keywords: sap datasphere, data warehouse cloud, dwc, data builder, business builder, analytic model, graphical view, sql view, transformation flow, replication flow, data flow, task chain, remote table, local table, sap btp data warehouse, datasphere connection, datasphere space, data access control, elastic compute node, sap analytics cloud integration, datasphere cli, data products, data marketplace, catalog, governance license: GPL-3.0 metadata: version: 2.1.0 last_verified: 2025-12-28

SAP Datasphere Skill

Table of Contents

• Overview
• Quick Reference
  • Core Components
  • Object Types
• Data Builder
  • Graphical Views
  • SQL Views
  • Tables
  • Flows
  • Task Chains
• Business Builder
• Analytic Models
• Connections
• Space Management
• Data Access Control
• Monitoring
• CLI Reference
• Data Products & Marketplace
• Catalog & Governance
• Content Transport
• Common Issues
• Bundled Resources
• Documentation Links

Overview

SAP Datasphere is SAP's cloud-native data warehouse solution on SAP Business Technology Platform (BTP). This skill provides comprehensive guidance for data acquisition, preparation, modeling, administration, and integration.

Use this skill when:

• Creating data warehouses on SAP BTP
• Building analytic models for SAP Analytics Cloud
• Setting up data flows, replication flows, or transformation flows
• Configuring connections to SAP or third-party systems
• Managing spaces, users, and access controls
• Implementing real-time data replication
• Monitoring data integration tasks

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Quick Reference

Core Components

Component	Purpose	Key Objects
Data Builder	Data acquisition & preparation	Views, Tables, Flows, Task Chains
Business Builder	Semantic layer modeling	Business Entities, Fact Models, Consumption Models
Analytic Model	Analytics-ready structures	Dimensions, Facts, Measures, Hierarchies
Connections	External data sources	40+ connection types
Spaces	Logical data containers	Storage, Users, Objects

Object Types

Views:

• Graphical View: Visual data modeling with drag-and-drop
• SQL View: SQL-based view definitions
• Analytic Model: Analytics-optimized semantic layer

Tables:

• Local Table: Data stored in Datasphere
• Remote Table: Virtual access to external data
• Local Table (File): Object store-based storage

Flows:

• Data Flow: ETL transformations
• Replication Flow: Data replication from sources
• Transformation Flow: Delta-aware transformations

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Data Builder

Graphical Views

Create views visually by dragging sources and adding transformations.

Supported Operations:

• Join: Inner, Left Outer, Right Outer, Full Outer, Cross
• Union: Combine multiple sources
• Projection: Select/rename columns
• Filter: Row-level filtering
• Aggregation: Group by with aggregates
• Calculated Columns: Derived values

Best Practices:

• Use input parameters for dynamic filtering
• Apply data access controls for row-level security
• Enable persistence for frequently accessed views
• Use lineage analysis to understand dependencies

For detailed graphical view operations, see references/graphical-sql-views.md.

SQL Views

Create views using SQL or SQLScript.

-- Basic SQL View
SELECT
    customer_id,
    customer_name,
    SUM(order_amount) AS total_orders
FROM orders
GROUP BY customer_id, customer_name

SQLScript Support:

• Table variables
• Scalar variables
• Control flow (IF, WHILE, FOR)
• Exception handling

For SQL/SQLScript reference, see references/graphical-sql-views.md.

Data Flows

ETL pipelines for data transformation and loading.

Operators:

• Source: Remote/local tables, views
• Target: Local tables
• Join, Union, Projection, Filter, Aggregation
• Script: Python custom logic
• Calculated Columns

Execution:

• Manual run or scheduled via task chains
• Delta capture for incremental loads
• Input parameters for runtime configuration

For data flow details, see references/data-acquisition-preparation.md.

Replication Flows

Replicate data from source systems to Datasphere or external targets.

Supported Sources:

• SAP S/4HANA (Cloud/On-Premise)
• SAP BW/4HANA
• SAP ECC
• ABAP-based systems
• Cloud storage (S3, Azure Blob, GCS)
• Kafka/Confluent
• SFTP

Supported Targets:

• SAP Datasphere (local tables)
• Apache Kafka
• Google BigQuery
• Cloud storage providers
• SAP Signavio

Load Types:

• Initial Load: Full data extraction
• Delta Load: Changed data only
• Real-Time: Continuous replication

For replication flow configuration, see references/data-acquisition-preparation.md.

Transformation Flows

Delta-aware transformations with automatic change propagation.

Key Features:

• Automatic delta detection
• Target table management
• Graphical or SQL view as source
• Run modes: Start, Delete, Truncate

For transformation flow details, see references/data-acquisition-preparation.md.

Task Chains

Orchestrate multiple tasks in sequence or parallel.

Supported Tasks:

• Data flows
• Replication flows
• Transformation flows
• Remote table replication
• View persistence
• Open SQL procedures
• API tasks
• BW Bridge process chains

Features:

• Parallel execution branches
• Input parameters
• Email notifications
• Nested task chains
• Scheduling (simple or cron)

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Data Modeling

Analytic Models

Create analytics-ready semantic models for SAP Analytics Cloud.

Components:

• Fact: Contains measures (quantitative data)
• Dimension: Categorizes data (master data)
• Measure: Quantifiable metrics
• Hierarchy: Navigation structures
• Variable: Runtime parameters

Creating an Analytic Model:

1. Add a fact source (view or table)
2. Add dimension associations
3. Define measures with aggregation
4. Configure variables for filtering
5. Set data access controls

For detailed modeling guidance, see references/data-modeling.md.

Dimensions

Categorize and filter analytical data.

Types:

• Standard: Basic categorical data
• Time: Calendar-based filtering
• Fiscal Time: Custom fiscal calendars
• Text Entity: Multilingual labels

Features:

• Hierarchies (level-based, parent-child)
• Time dependency (SCD Type 2)
• Compound keys
• Associated text entities

Measures

Quantifiable values for analysis.

Types:

• Simple: Direct aggregation
• Calculated: Derived from other measures
• Restricted: Filtered aggregation
• Currency Conversion: Dynamic conversion
• Unit Conversion: Dynamic conversion
• Count Distinct: Unique value count
• Non-Cumulative: Point-in-time values

Aggregation Types:

• SUM, MIN, MAX, COUNT, AVG
• Exception aggregation for non-additive scenarios

For measure configuration, see references/data-modeling.md.

Business Builder

Create business-oriented semantic models.

Objects:

• Business Entity: Reusable dimension/fact definitions
• Fact Model: Combines business entities
• Consumption Model: Analytics-ready model
• Authorization Scenario: Row-level security

For Business Builder details, see references/data-modeling.md.

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Connectivity

Connection Types

SAP Datasphere supports 40+ connection types.

SAP Systems:

• SAP S/4HANA Cloud/On-Premise
• SAP BW/4HANA (Model Transfer)
• SAP BW Bridge
• SAP ECC
• SAP HANA (Cloud/On-Premise)
• SAP SuccessFactors
• SAP Fieldglass
• SAP Marketing Cloud
• SAP Signavio

Cloud Platforms:

• Amazon S3, Athena, Redshift
• Google Cloud Storage, BigQuery
• Microsoft Azure Blob, Data Lake, SQL Database
• Microsoft OneLake

Databases:

• Oracle
• Microsoft SQL Server
• Generic JDBC

Streaming:

• Apache Kafka
• Confluent

Other:

• Generic OData, HTTP, SFTP
• Adverity, Precog
• SAP Open Connectors

For connection configuration, see references/connectivity.md.

Connection Features

Feature	Description
Remote Tables	Virtual data access
Data Flows	ETL transformation
Replication Flows	Data replication
Model Import	BW/4HANA model transfer

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Administration

Spaces

Logical containers for data and objects.

Configuration:

• Storage allocation (disk + in-memory)
• User access and roles
• Priority and statement limits
• Workload management

Operations:

• Create, copy, delete spaces
• Export/import space data
• Command-line management (datasphere CLI)

For space management, see references/administration.md.

Users and Roles

Standard Roles:

• DW Administrator
• DW Space Administrator
• DW Integrator
• DW Modeler
• DW Viewer

Scoped Roles:

• Space-specific permissions
• Custom privilege combinations

Authentication:

• SAP Cloud Identity Services
• Custom SAML IdP
• OAuth 2.0 clients

For user management, see references/administration.md.

Monitoring

Capabilities:

• Capacity monitoring (storage, memory, compute)
• Audit logs (database operations)
• Activity logs (object changes)
• Task logs (flow executions)

Database Analysis:

• Create analysis users for debugging
• Monitor HANA views
• Stop running statements

For monitoring details, see references/administration.md.

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Data Integration Monitor

Remote Tables

Operations:

• Replicate data (full/delta/real-time)
• Partition data loads
• Create statistics
• Monitor queries

Real-Time Replication

Features:

• Continuous change capture
• Pause/resume capability
• Automatic recovery
• Watermark tracking

View Persistence

Options:

• Scheduled refresh
• On-demand refresh
• Partition management
• Memory optimization

For monitoring details, see references/data-integration-monitor.md.

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CLI Reference

Datasphere CLI Overview

The datasphere CLI enables command-line administration and automation.

Installation:

npm install -g @sap/datasphere-cli

Authentication:

# Interactive login
datasphere config auth login

# Service key (CI/CD)
datasphere config auth login --service-key-path ./key.json

Core Commands:

Command	Purpose
datasphere spaces list	List all spaces
datasphere spaces create	Create a space
datasphere objects export	Export objects
datasphere objects import	Import objects
datasphere tasks run	Execute task chains
datasphere marketplace list	List marketplace products

CI/CD Integration:

# Export and import workflow
datasphere objects export --space DEV --output-file package.zip
datasphere objects import --space PROD --input-file package.zip --overwrite

For complete CLI reference, see references/cli-commands.md.

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Data Products & Marketplace

Creating Data Products

Package curated data for internal or external consumption:

1. Plan: Define purpose, target consumers, contents
2. Prepare: Create views/models, set semantic usage, document
3. Configure: Set visibility, access controls, terms
4. Publish: Make available in marketplace

Product Components:

• Core assets (views, models, entities)
• Documentation and sample queries
• Governance metadata (owner, quality score, SLA)

Data Marketplace

Discover and consume published data products:

• Search: Find by category, provider, quality
• Request Access: Submit justification, await approval
• Consume: Use in views or SAC stories

For complete marketplace guidance, see references/data-products-marketplace.md.

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Catalog & Governance

Data Catalog Features

Centralized discovery and governance:

• Asset Discovery: Search all data objects with metadata
• Glossary: Standardized business term definitions
• Data Quality: Automated quality rules and scoring
• Lineage: Trace data from source to consumption
• Classification: Sensitivity levels and compliance tags

Governance Workflow

Create Object → Add Metadata → Link Terms → Quality Check → Approve → Publish

Roles:

• Data Owner: Business accountability
• Data Steward: Quality and metadata management
• Data Custodian: Technical implementation

For detailed governance guidance, see references/catalog-governance.md.

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Data Access Controls

Implement row-level security.

Types:

• Single Values: Simple value matching
• Operator and Values: Complex conditions
• Hierarchy: Node-based filtering
• Hierarchy with Directory: Hierarchical permissions

Application:

• Apply to views or analytic models
• Based on user attributes
• Import from SAP BW Analysis Authorizations

For security configuration, see references/data-access-security.md.

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Content Transport

Move content between tenants.

Methods:

• Export/Import packages
• SAP Cloud Transport Management
• CSN/JSON file export

Package Contents:

• Views, tables, flows
• Connections (metadata only)
• Spaces configuration

For transport procedures, see references/content-transport.md.

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Common Errors and Solutions

Error	Cause	Solution
Deployment failed	Circular dependency	Check object dependencies
Connection timeout	Network/firewall	Verify Cloud Connector/IP allowlist
Replication stuck	Source lock	Check source system status
Out of memory	Large view	Enable persistence or partitioning
Permission denied	Missing role	Verify space membership and privileges

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Bundled Resources

Reference Documentation

Core Data Builder:

1. references/data-acquisition-preparation.md - Data flows, replication flows, transformation flows, and table management
2. references/graphical-sql-views.md - Graphical views, SQL views, E-R models, and intelligent lookups
3. references/data-modeling.md - Business Builder entities, analytic models, dimensions, measures, and hierarchies

Connectivity & Integration: 4. references/connectivity.md - All 40+ connection types including SAP systems, cloud providers, and streaming platforms 5. references/data-integration-monitor.md - Task scheduling, monitoring, real-time replication, and delta mechanisms

Administration & Security: 6. references/administration.md - Tenant management, space configuration, user roles, and elastic compute nodes 7. references/data-access-security.md - Row-level security, DAC configurations, and authorization scenarios 8. references/content-transport.md - Package export/import, transport management, and tenant migration

CLI & Automation: 9. references/cli-commands.md - Complete CLI reference, authentication, CI/CD integration patterns

Marketplace & Governance: 10. references/data-products-marketplace.md - Creating and consuming data products, provider workflows, pricing 11. references/catalog-governance.md - Data catalog, glossary, quality rules, lineage, classification

Best Practices & Updates: 12. references/best-practices-patterns.md - Architecture patterns, naming conventions, performance optimization, checklists 13. references/whats-new-2025.md - Q1-Q4 2025 features, Generic HTTP, REST API tasks, deprecations

MCP Integration: 14. references/mcp-tools-reference.md - Complete MCP tool reference, 45 tools across 8 categories, API documentation, authentication patterns 15. references/mcp-use-cases.md - 8 real-world use cases with personas, time savings, and ROI analysis ($159K+/year savings)

Plugin Components

This plugin includes 3 specialized agents, 4 slash commands, and validation hooks:

Agents (in agents/):

• datasphere-modeler - Data Builder tasks, views, flows, analytic models
• datasphere-integration-advisor - Connectivity, replication, data integration
• datasphere-admin-helper - Space management, security, monitoring

Commands (in commands/):

• /datasphere-space-template - Generate space configurations
• /datasphere-view-template - Generate view templates (graphical/SQL)
• /datasphere-connection-guide - Step-by-step connection setup
• /datasphere-cli - CLI command reference and examples

Hooks (in hooks/):

• PreToolUse validation for SQL/SQLScript code quality
• PostToolUse suggestions for persistence and optimization

MCP Integration

This skill integrates with the SAP Datasphere MCP Server (@mariodefe/sap-datasphere-mcp) providing 45 tools for live tenant interaction.

MCP Tools

The MCP server enables:

• Direct Queries: Execute SQL and smart queries on live data
• Metadata Access: Inspect tables, views, and analytic models
• User Management: Create, update, delete database users
• Catalog Search: Find assets by name or column
• Connection Testing: Verify connectivity and tenant info
• Data Profiling: Analyze column distributions

See /datasphere-mcp-tools command for complete tool list.

Authentication

OAuth 2.0 Client Credentials with automatic token refresh.

Required environment variables:

• DATASPHERE_BASE_URL
• DATASPHERE_CLIENT_ID
• DATASPHERE_CLIENT_SECRET
• DATASPHERE_TOKEN_URL

Performance

• Sub-100ms metadata queries (cached)
• 100-500ms catalog operations
• 500-2,000ms OData queries
• Batch processing up to 50,000 records

File Structure

plugins/sap-datasphere/
├── .claude-plugin/
│   └── plugin.json
├── .mcp.json                         # MCP server configuration
├── agents/
│   ├── datasphere-modeler.md
│   ├── datasphere-integration-advisor.md
│   └── datasphere-admin-helper.md
├── commands/
│   ├── datasphere-space-template.md
│   ├── datasphere-view-template.md
│   ├── datasphere-connection-guide.md
│   ├── datasphere-cli.md
│   └── datasphere-mcp-tools.md       # MCP tools reference
├── hooks/
│   └── hooks.json
└── skills/
    └── sap-datasphere/
        ├── .claude-plugin/
        │   └── plugin.json
        ├── SKILL.md
        ├── README.md
        └── references/
            ├── data-acquisition-preparation.md
            ├── data-modeling.md
            ├── graphical-sql-views.md
            ├── connectivity.md
            ├── administration.md
            ├── data-integration-monitor.md
            ├── data-access-security.md
            ├── content-transport.md
            ├── cli-commands.md
            ├── data-products-marketplace.md
            ├── catalog-governance.md
            ├── best-practices-patterns.md
            ├── whats-new-2025.md
            └── mcp-tools-reference.md    # MCP technical reference

Documentation Links

• SAP Help Portal: https://help.sap.com/docs/SAP_DATASPHERE
• Source Repository: https://github.com/SAP-docs/sap-datasphere
• SAP Community: https://community.sap.com/topics/datasphere
• API Reference: https://api.sap.com/package/saaborddatasphere

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Version: 2.1.0 | Last Verified: 2025-12-28