sap-datasphere

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SAP Datasphere Skill

SAP Datasphere 技能

Overview

概述

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

SAP Datasphere是SAP Business Technology Platform (BTP)上的云原生数据仓库解决方案。本技能为数据获取、准备、建模、管理和集成提供全面指导。

适用场景:

在SAP BTP上创建数据仓库
为SAP Analytics Cloud构建分析模型
设置数据流、复制流或转换流
配置与SAP或第三方系统的连接
管理空间、用户和访问控制
实施实时数据复制
监控数据集成任务

Quick Reference

快速参考

Core Components

核心组件

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

组件	用途	关键对象
Data Builder	数据获取与准备	视图、表、流、任务链
Business Builder	语义层建模	业务实体、事实模型、消费模型
Analytic Model	分析就绪结构	维度、事实、度量、层级
Connections	外部数据源	40余种连接类型
Spaces	逻辑数据容器	存储、用户、对象

Object Types

对象类型

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

视图:

Graphical View: 拖拽式可视化数据建模
SQL View: 基于SQL的视图定义
Analytic Model: 优化分析的语义层

表:

Local Table: 存储在Datasphere中的数据
Remote Table: 对外部数据的虚拟访问
Local Table (File): 基于对象存储的表

流:

Data Flow: ETL转换
Replication Flow: 从数据源复制数据
Transformation Flow: 支持增量的转换

Data Builder

Graphical Views

图形化视图

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

通过拖拽数据源并添加转换来可视化创建视图。

支持的操作:

连接: 内连接、左外连接、右外连接、全外连接、交叉连接
联合: 合并多个数据源
投影: 选择/重命名列
过滤: 行级过滤
聚合: 分组聚合
计算列: 派生值

最佳实践:

使用输入参数实现动态过滤
应用数据访问控制实现行级安全
为频繁访问的视图启用持久化
使用血缘分析理解依赖关系

图形化视图操作详情，请参阅

references/graphical-sql-views.md

。

SQL Views

SQL视图

Create views using SQL or SQLScript.

sql

-- 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

使用SQL或SQLScript创建视图。

sql

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

SQLScript支持:

表变量
标量变量
控制流（IF、WHILE、FOR）
异常处理

SQL/SQLScript参考，请参阅

references/graphical-sql-views.md

。

Data Flows

数据流

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

用于数据转换和加载的ETL管道。

操作符:

源: 远程/本地表、视图
目标: 本地表
连接、联合、投影、过滤、聚合
脚本: Python自定义逻辑
计算列

执行:

手动运行或通过任务链调度
增量捕获实现增量加载
输入参数用于运行时配置

数据流详情，请参阅

references/data-acquisition-preparation.md

。

Replication Flows

复制流

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

将数据从源系统复制到Datasphere或外部目标。

支持的源系统:

SAP S/4HANA（云/本地部署）
SAP BW/4HANA
SAP ECC
基于ABAP的系统
云存储（S3、Azure Blob、GCS）
Kafka/Confluent
SFTP

支持的目标系统:

SAP Datasphere（本地表）
Apache Kafka
Google BigQuery
云存储提供商
SAP Signavio

加载类型:

初始加载: 全量数据提取
增量加载: 仅提取变更数据
实时: 持续复制

复制流配置，请参阅

references/data-acquisition-preparation.md

。

Transformation Flows

转换流

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

支持增量的转换，可自动传播变更。

关键特性:

自动增量检测
目标表管理
图形化或SQL视图作为源
运行模式: 启动、删除、截断

转换流详情，请参阅

references/data-acquisition-preparation.md

。

Task Chains

任务链

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)

按顺序或并行编排多个任务。

支持的任务:

数据流
复制流
转换流
远程表复制
视图持久化
开放SQL过程
API任务
BW Bridge流程链

特性:

并行执行分支
输入参数
邮件通知
嵌套任务链
调度（简单或cron表达式）

Data Modeling

数据建模

Analytic Models

分析模型

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:

Add a fact source (view or table)
Add dimension associations
Define measures with aggregation
Configure variables for filtering
Set data access controls

For detailed modeling guidance, see

references/data-modeling.md

为SAP Analytics Cloud创建分析就绪的语义模型。

组件:

Fact: 包含度量（量化数据）
Dimension: 数据分类（主数据）
Measure: 可量化指标
Hierarchy: 导航结构
Variable: 运行时参数

创建分析模型步骤:

添加事实源（视图或表）
添加维度关联
定义带聚合的度量
配置过滤变量
设置数据访问控制

建模详细指南，请参阅

references/data-modeling.md

。

Dimensions

维度

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

对分析数据进行分类和过滤。

类型:

标准: 基础分类数据
时间: 基于日历的过滤
财年时间: 自定义财年日历
文本实体: 多语言标签

特性:

层级（基于级别、父子关系）
时间依赖性（SCD Type 2）
复合键
关联文本实体

Measures

度量

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

用于分析的可量化值。

类型:

简单: 直接聚合
计算: 从其他度量派生
受限: 过滤后聚合
货币转换: 动态转换
单位转换: 动态转换
去重计数: 唯一值计数
非累积: 时间点值

聚合类型:

SUM、MIN、MAX、COUNT、AVG
针对非累加场景的异常聚合

度量配置，请参阅

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

创建面向业务的语义模型。

对象:

Business Entity: 可复用的维度/事实定义
Fact Model: 组合业务实体
Consumption Model: 分析就绪模型
Authorization Scenario: 行级安全

Business Builder详情，请参阅

references/data-modeling.md

。

Connectivity

连接性

Connection Types

连接类型

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

SAP Datasphere支持40余种连接类型。

SAP系统:

SAP S/4HANA Cloud/本地部署
SAP BW/4HANA（模型传输）
SAP BW Bridge
SAP ECC
SAP HANA（云/本地部署）
SAP SuccessFactors
SAP Fieldglass
SAP Marketing Cloud
SAP Signavio

云平台:

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

数据库:

Oracle
Microsoft SQL Server
通用JDBC

流处理:

Apache Kafka
Confluent

其他:

通用OData、HTTP、SFTP
Adverity、Precog
SAP Open Connectors

连接配置，请参阅

references/connectivity.md

。

Connection Features

连接特性

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

特性	描述
Remote Tables	虚拟数据访问
Data Flows	ETL转换
Replication Flows	数据复制
Model Import	BW/4HANA模型传输

Administration

管理

Spaces

空间

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

数据和对象的逻辑容器。

配置:

存储分配（磁盘+内存）
用户访问和角色
优先级和语句限制
工作负载管理

操作:

创建、复制、删除空间
导出/导入空间数据
命令行管理（datasphere CLI）

空间管理，请参阅

references/administration.md

。

Users and Roles

用户和角色

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

标准角色:

DW Administrator
DW Space Administrator
DW Integrator
DW Modeler
DW Viewer

范围角色:

空间特定权限
自定义权限组合

认证:

SAP Cloud Identity Services
自定义SAML IdP
OAuth 2.0客户端

用户管理，请参阅

references/administration.md

。

Monitoring

监控

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

功能:

容量监控（存储、内存、计算）
审计日志（数据库操作）
活动日志（对象变更）
任务日志（流执行）

数据库分析:

创建分析用户用于调试
监控HANA视图
停止运行中的语句

监控详情，请参阅

references/administration.md

。

Data Integration Monitor

数据集成监控

Remote Tables

远程表

Operations:

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

操作:

复制数据（全量/增量/实时）
分区数据加载
创建统计信息
监控查询

Real-Time Replication

实时复制

Features:

Continuous change capture
Pause/resume capability
Automatic recovery
Watermark tracking

特性:

持续变更捕获
暂停/恢复功能
自动恢复
水印跟踪

View Persistence

视图持久化

Options:

Scheduled refresh
On-demand refresh
Partition management
Memory optimization

For monitoring details, see

references/data-integration-monitor.md

选项:

调度刷新
按需刷新
分区管理
内存优化

监控详情，请参阅

references/data-integration-monitor.md

。

CLI Reference

CLI参考

Datasphere CLI Overview

Datasphere CLI概述

The

datasphere

CLI enables command-line administration and automation.

Installation:

bash

npm install -g @sap/datasphere-cli

Authentication:

bash

undefined

datasphere

CLI支持命令行管理和自动化。

安装:

bash

npm install -g @sap/datasphere-cli

认证:

bash

undefined

Interactive login

交互式登录

datasphere config auth login

Service key (CI/CD)

服务密钥（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**:
```bash

datasphere config auth login --service-key-path ./key.json


**核心命令**:

| 命令 | 用途 |
|---------|---------|
| `datasphere spaces list` | 列出所有空间 |
| `datasphere spaces create` | 创建空间 |
| `datasphere objects export` | 导出对象 |
| `datasphere objects import` | 导入对象 |
| `datasphere tasks run` | 执行任务链 |
| `datasphere marketplace list` | 列出市场产品 |

**CI/CD集成**:
```bash

Export and import workflow

导出和导入工作流

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`.

---

datasphere objects export --space DEV --output-file package.zip datasphere objects import --space PROD --input-file package.zip --overwrite


完整CLI参考，请参阅`references/cli-commands.md`。

---

Data Products & Marketplace

数据产品与市场

Creating Data Products

创建数据产品

Package curated data for internal or external consumption:

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

Product Components:

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

打包精选数据供内部或外部使用:

规划: 定义用途、目标用户、内容
准备: 创建视图/模型、设置语义用途、添加文档
配置: 设置可见性、访问控制、条款
发布: 在市场中发布

产品组件:

核心资产（视图、模型、实体）
文档和示例查询
治理元数据（所有者、质量评分、SLA）

Data Marketplace

数据市场

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

发现和使用已发布的数据产品:

搜索: 按类别、提供商、质量查找
申请访问: 提交理由，等待审批
使用: 在视图或SAC故事中使用

市场完整指南，请参阅

references/data-products-marketplace.md

。

Catalog & Governance

目录与治理

Data Catalog Features

数据目录特性

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

集中式发现和治理:

资产发现: 搜索带元数据的所有数据对象
术语表: 标准化业务术语定义
数据质量: 自动化质量规则和评分
血缘: 跟踪数据从源到消费的路径
分类: 敏感度级别和合规标签

Governance Workflow

治理工作流

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

创建对象 → 添加元数据 → 关联术语 → 质量检查 → 审批 → 发布

角色:

数据所有者: 业务负责人
数据管家: 质量和元数据管理
数据管理员: 技术实施

治理详细指南，请参阅

references/catalog-governance.md

。

Data Access Controls

数据访问控制

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

实施行级安全。

类型:

单值: 简单值匹配
操作符与值: 复杂条件
层级: 基于节点的过滤
层级与目录: 层级权限

应用:

应用于视图或分析模型
基于用户属性
从SAP BW分析授权导入

安全配置，请参阅

references/data-access-security.md

。

Content Transport

内容传输

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

在租户间移动内容。

方法:

导出/导入包
SAP Cloud Transport Management
CSN/JSON文件导出

包内容:

视图、表、流
连接（仅元数据）
空间配置

传输流程，请参阅

references/content-transport.md

。

Common Errors and Solutions

常见错误与解决方案

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

错误	原因	解决方案
部署失败	循环依赖	检查对象依赖关系
连接超时	网络/防火墙	验证Cloud Connector/IP白名单
复制停滞	源系统锁定	检查源系统状态
内存不足	视图过大	启用持久化或分区
权限拒绝	缺少角色	验证空间成员身份和权限

Bundled Resources

捆绑资源

Reference Documentation

参考文档

Core Data Builder:

references/data-acquisition-preparation.md
- Data flows, replication flows, transformation flows, and table management
references/graphical-sql-views.md
- Graphical views, SQL views, E-R models, and intelligent lookups
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)

核心Data Builder:

references/data-acquisition-preparation.md
- 数据流、复制流、转换流和表管理
references/graphical-sql-views.md
- 图形化视图、SQL视图、E-R模型和智能查找
references/data-modeling.md
- Business Builder实体、分析模型、维度、度量和层级

连接性与集成: 4. references/connectivity.md
- 40余种连接类型，包括SAP系统、云提供商和流处理平台 5. references/data-integration-monitor.md
- 任务调度、监控、实时复制和增量机制

管理与安全: 6. references/administration.md
- 租户管理、空间配置、用户角色和弹性计算节点 7. references/data-access-security.md
- 行级安全、DAC配置和授权场景 8. references/content-transport.md
- 包导出/导入、传输管理和租户迁移

CLI与自动化: 9. references/cli-commands.md
- 完整CLI参考、认证、CI/CD集成模式

市场与治理: 10. references/data-products-marketplace.md
- 创建和使用数据产品、提供商工作流、定价 11. references/catalog-governance.md
- 数据目录、术语表、质量规则、血缘、分类

最佳实践与更新: 12. references/best-practices-patterns.md
- 架构模式、命名规范、性能优化、检查清单 13. references/whats-new-2025.md
- 2025年Q1-Q4特性、通用HTTP、REST API任务、弃用内容

MCP集成: 14. references/mcp-tools-reference.md
- 完整MCP工具参考、8个类别共45个工具、API文档、认证模式 15. references/mcp-use-cases.md
- 8个真实场景用例、角色、时间节省、ROI分析（每年节省15.9万美元以上）

Plugin Components

插件组件

This plugin includes 3 specialized agents, 5 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

本插件包含3个专用Agent、5个斜杠命令和验证钩子:

Agents（位于

agents/

）:

```
datasphere-modeler
```
- Data Builder任务、视图、流、分析模型
```
datasphere-integration-advisor
```
- 连接性、复制、数据集成
```
datasphere-admin-helper
```
- 空间管理、安全、监控

Commands（位于

commands/

）:

```
/datasphere-space-template
```
- 生成空间配置
```
/datasphere-view-template
```
- 生成视图模板（图形化/SQL）
```
/datasphere-connection-guide
```
- 分步连接设置
```
/datasphere-cli
```
- CLI命令参考和示例

Hooks（位于

hooks/

）:

SQL/SQLScript代码质量的PreToolUse验证
持久化和优化的PostToolUse建议

MCP Integration

MCP集成

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

本技能与SAP Datasphere MCP Server (@mariodefe/sap-datasphere-mcp)集成，提供45个工具用于与租户实时交互。

MCP Tools

MCP工具

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.

MCP服务器支持:

直接查询: 在实时数据上执行SQL和智能查询
元数据访问: 检查表、视图和分析模型
用户管理: 创建、更新、删除数据库用户
目录搜索: 按名称或列查找资产
连接测试: 验证连接性和租户信息
数据剖析: 分析列分布

完整工具列表请查看

/datasphere-mcp-tools

命令。

Authentication

认证

OAuth 2.0 Client Credentials with automatic token refresh.

Required environment variables:

```
DATASPHERE_BASE_URL
```
```
DATASPHERE_CLIENT_ID
```
```
DATASPHERE_CLIENT_SECRET
```
```
DATASPHERE_TOKEN_URL
```

带自动令牌刷新的OAuth 2.0客户端凭证。

所需环境变量:

```
DATASPHERE_BASE_URL
```
```
DATASPHERE_CLIENT_ID
```
```
DATASPHERE_CLIENT_SECRET
```
```
DATASPHERE_TOKEN_URL
```

Performance

性能

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

元数据查询（缓存）: 小于100ms
目录操作: 100-500ms
OData查询: 500-2000ms
批量处理: 最多50000条记录

File Structure

文件结构

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

plugins/sap-datasphere/
├── .claude-plugin/
│   └── plugin.json
├── .mcp.json                         # MCP服务器配置
├── 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工具参考
├── 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技术参考

Documentation Links

文档链接

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

SAP帮助门户: https://help.sap.com/docs/SAP_DATASPHERE
源码仓库: https://github.com/SAP-docs/sap-datasphere
SAP社区: https://community.sap.com/topics/datasphere
API参考: https://api.sap.com/package/saaborddatasphere

版本: 2.1.0 | 最后验证: 2025-12-28

sap-datasphere

Original

Translation

SAP Datasphere Skill

SAP Datasphere 技能

Table of Contents

目录

Overview

概述

Quick Reference

快速参考

Core Components

核心组件

Object Types

对象类型

Data Builder

Data Builder

Graphical Views

图形化视图

SQL Views

SQL视图

Data Flows

数据流

Replication Flows

复制流

Transformation Flows

转换流

Task Chains

任务链

Data Modeling

数据建模

Analytic Models

分析模型

Dimensions

维度

Measures

度量

Business Builder

Business Builder

Connectivity

连接性

Connection Types

连接类型

Connection Features

连接特性

Administration

管理

Spaces

空间

Users and Roles

用户和角色

Monitoring

监控

Data Integration Monitor

数据集成监控

Remote Tables

远程表

Real-Time Replication

实时复制

View Persistence

视图持久化

CLI Reference

CLI参考

Datasphere CLI Overview

Datasphere CLI概述

Interactive login

交互式登录

Service key (CI/CD)

服务密钥（CI/CD）

Export and import workflow

导出和导入工作流

Data Products & Marketplace

数据产品与市场

Creating Data Products

创建数据产品

Data Marketplace

数据市场

Catalog & Governance

目录与治理

Data Catalog Features