SAP Datasphere Skill
Table of Contents
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Overview
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Quick Reference
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Core Components
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Object Types
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Data Builder
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Graphical Views
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SQL Views
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Tables
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Flows
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Task Chains
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Business Builder
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Analytic Models
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Connections
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Space Management
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Data Access Control
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Monitoring
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CLI Reference
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Data Products & Marketplace
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Catalog & Governance
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Content Transport
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Common Issues
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Bundled Resources
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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:
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Creating data warehouses on SAP BTP
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Building analytic models for SAP Analytics Cloud
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Setting up data flows, replication flows, or transformation flows
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Configuring connections to SAP or third-party systems
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Managing spaces, users, and access controls
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Implementing real-time data replication
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Monitoring data integration tasks
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:
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Graphical View: Visual data modeling with drag-and-drop
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SQL View: SQL-based view definitions
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Analytic Model: Analytics-optimized semantic layer
Tables:
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Local Table: Data stored in Datasphere
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Remote Table: Virtual access to external data
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Local Table (File): Object store-based storage
Flows:
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Data Flow: ETL transformations
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Replication Flow: Data replication from sources
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Transformation Flow: Delta-aware transformations
Data Builder
Graphical Views
Create views visually by dragging sources and adding transformations.
Supported Operations:
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Join: Inner, Left Outer, Right Outer, Full Outer, Cross
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Union: Combine multiple sources
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Projection: Select/rename columns
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Filter: Row-level filtering
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Aggregation: Group by with aggregates
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Calculated Columns: Derived values
Best Practices:
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Use input parameters for dynamic filtering
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Apply data access controls for row-level security
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Enable persistence for frequently accessed views
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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:
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Table variables
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Scalar variables
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Control flow (IF, WHILE, FOR)
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Exception handling
For SQL/SQLScript reference, see references/graphical-sql-views.md .
Data Flows
ETL pipelines for data transformation and loading.
Operators:
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Source: Remote/local tables, views
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Target: Local tables
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Join, Union, Projection, Filter, Aggregation
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Script: Python custom logic
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Calculated Columns
Execution:
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Manual run or scheduled via task chains
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Delta capture for incremental loads
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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:
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SAP S/4HANA (Cloud/On-Premise)
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SAP BW/4HANA
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SAP ECC
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ABAP-based systems
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Cloud storage (S3, Azure Blob, GCS)
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Kafka/Confluent
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SFTP
Supported Targets:
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SAP Datasphere (local tables)
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Apache Kafka
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Google BigQuery
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Cloud storage providers
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SAP Signavio
Load Types:
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Initial Load: Full data extraction
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Delta Load: Changed data only
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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:
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Automatic delta detection
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Target table management
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Graphical or SQL view as source
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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:
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Data flows
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Replication flows
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Transformation flows
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Remote table replication
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View persistence
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Open SQL procedures
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API tasks
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BW Bridge process chains
Features:
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Parallel execution branches
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Input parameters
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Email notifications
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Nested task chains
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Scheduling (simple or cron)
Data Modeling
Analytic Models
Create analytics-ready semantic models for SAP Analytics Cloud.
Components:
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Fact: Contains measures (quantitative data)
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Dimension: Categorizes data (master data)
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Measure: Quantifiable metrics
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Hierarchy: Navigation structures
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Variable: Runtime parameters
Creating an Analytic Model:
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Add a fact source (view or table)
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Add dimension associations
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Define measures with aggregation
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Configure variables for filtering
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Set data access controls
For detailed modeling guidance, see references/data-modeling.md .
Dimensions
Categorize and filter analytical data.
Types:
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Standard: Basic categorical data
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Time: Calendar-based filtering
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Fiscal Time: Custom fiscal calendars
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Text Entity: Multilingual labels
Features:
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Hierarchies (level-based, parent-child)
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Time dependency (SCD Type 2)
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Compound keys
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Associated text entities
Measures
Quantifiable values for analysis.
Types:
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Simple: Direct aggregation
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Calculated: Derived from other measures
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Restricted: Filtered aggregation
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Currency Conversion: Dynamic conversion
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Unit Conversion: Dynamic conversion
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Count Distinct: Unique value count
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Non-Cumulative: Point-in-time values
Aggregation Types:
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SUM, MIN, MAX, COUNT, AVG
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Exception aggregation for non-additive scenarios
For measure configuration, see references/data-modeling.md .
Business Builder
Create business-oriented semantic models.
Objects:
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Business Entity: Reusable dimension/fact definitions
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Fact Model: Combines business entities
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Consumption Model: Analytics-ready model
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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:
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SAP S/4HANA Cloud/On-Premise
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SAP BW/4HANA (Model Transfer)
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SAP BW Bridge
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SAP ECC
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SAP HANA (Cloud/On-Premise)
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SAP SuccessFactors
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SAP Fieldglass
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SAP Marketing Cloud
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SAP Signavio
Cloud Platforms:
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Amazon S3, Athena, Redshift
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Google Cloud Storage, BigQuery
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Microsoft Azure Blob, Data Lake, SQL Database
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Microsoft OneLake
Databases:
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Oracle
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Microsoft SQL Server
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Generic JDBC
Streaming:
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Apache Kafka
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Confluent
Other:
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Generic OData, HTTP, SFTP
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Adverity, Precog
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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
Administration
Spaces
Logical containers for data and objects.
Configuration:
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Storage allocation (disk + in-memory)
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User access and roles
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Priority and statement limits
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Workload management
Operations:
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Create, copy, delete spaces
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Export/import space data
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Command-line management (datasphere CLI)
For space management, see references/administration.md .
Users and Roles
Standard Roles:
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DW Administrator
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DW Space Administrator
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DW Integrator
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DW Modeler
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DW Viewer
Scoped Roles:
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Space-specific permissions
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Custom privilege combinations
Authentication:
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SAP Cloud Identity Services
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Custom SAML IdP
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OAuth 2.0 clients
For user management, see references/administration.md .
Monitoring
Capabilities:
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Capacity monitoring (storage, memory, compute)
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Audit logs (database operations)
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Activity logs (object changes)
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Task logs (flow executions)
Database Analysis:
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Create analysis users for debugging
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Monitor HANA views
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Stop running statements
For monitoring details, see references/administration.md .
Data Integration Monitor
Remote Tables
Operations:
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Replicate data (full/delta/real-time)
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Partition data loads
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Create statistics
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Monitor queries
Real-Time Replication
Features:
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Continuous change capture
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Pause/resume capability
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Automatic recovery
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Watermark tracking
View Persistence
Options:
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Scheduled refresh
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On-demand refresh
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Partition management
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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:
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 .
Data Products & Marketplace
Creating Data Products
Package curated data for internal or external consumption:
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Plan: Define purpose, target consumers, contents
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Prepare: Create views/models, set semantic usage, document
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Configure: Set visibility, access controls, terms
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Publish: Make available in marketplace
Product Components:
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Core assets (views, models, entities)
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Documentation and sample queries
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Governance metadata (owner, quality score, SLA)
Data Marketplace
Discover and consume published data products:
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Search: Find by category, provider, quality
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Request Access: Submit justification, await approval
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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:
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Asset Discovery: Search all data objects with metadata
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Glossary: Standardized business term definitions
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Data Quality: Automated quality rules and scoring
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Lineage: Trace data from source to consumption
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Classification: Sensitivity levels and compliance tags
Governance Workflow
Create Object → Add Metadata → Link Terms → Quality Check → Approve → Publish
Roles:
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Data Owner: Business accountability
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Data Steward: Quality and metadata management
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Data Custodian: Technical implementation
For detailed governance guidance, see references/catalog-governance.md .
Data Access Controls
Implement row-level security.
Types:
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Single Values: Simple value matching
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Operator and Values: Complex conditions
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Hierarchy: Node-based filtering
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Hierarchy with Directory: Hierarchical permissions
Application:
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Apply to views or analytic models
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Based on user attributes
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Import from SAP BW Analysis Authorizations
For security configuration, see references/data-access-security.md .
Content Transport
Move content between tenants.
Methods:
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Export/Import packages
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SAP Cloud Transport Management
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CSN/JSON file export
Package Contents:
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Views, tables, flows
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Connections (metadata only)
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Spaces configuration
For transport procedures, see references/content-transport.md .
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
Bundled Resources
Reference Documentation
Core Data Builder:
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references/data-acquisition-preparation.md
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Data flows, replication flows, transformation flows, and table management
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references/graphical-sql-views.md
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Graphical views, SQL views, E-R models, and intelligent lookups
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references/data-modeling.md
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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
- 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
- references/data-access-security.md
- Row-level security, DAC configurations, and authorization scenarios
- 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
- 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
- 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
- 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, 5 slash commands, and validation hooks:
Agents (in agents/ ):
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datasphere-modeler
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Data Builder tasks, views, flows, analytic models
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datasphere-integration-advisor
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Connectivity, replication, data integration
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datasphere-admin-helper
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Space management, security, monitoring
Commands (in commands/ ):
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/datasphere-space-template
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Generate space configurations
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/datasphere-view-template
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Generate view templates (graphical/SQL)
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/datasphere-connection-guide
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Step-by-step connection setup
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/datasphere-cli
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CLI command reference and examples
Hooks (in hooks/ ):
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PreToolUse validation for SQL/SQLScript code quality
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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:
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Direct Queries: Execute SQL and smart queries on live data
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Metadata Access: Inspect tables, views, and analytic models
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User Management: Create, update, delete database users
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Catalog Search: Find assets by name or column
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Connection Testing: Verify connectivity and tenant info
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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:
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DATASPHERE_BASE_URL
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DATASPHERE_CLIENT_ID
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DATASPHERE_CLIENT_SECRET
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DATASPHERE_TOKEN_URL
Performance
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Sub-100ms metadata queries (cached)
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100-500ms catalog operations
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500-2,000ms OData queries
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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
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SAP Help Portal: https://help.sap.com/docs/SAP_DATASPHERE
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Source Repository: https://github.com/SAP-docs/sap-datasphere
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SAP Community: https://community.sap.com/topics/datasphere
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API Reference: https://api.sap.com/package/saaborddatasphere
Version: 2.1.0 | Last Verified: 2025-12-28