Dherbe Digital Nova Skills Collection Sap Datasphere

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

Quick Reference

Core Components

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

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)

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.

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

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.

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.

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:

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.

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.

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.

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.

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.

Common Errors and Solutions

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

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

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