데이터 계보 에이전트 프롬프트
저장소와 플랫폼 정보를 넣으면 SQL 스크립트와 저장 프로시저를 분석해 테이블 관계, 데이터 흐름, 변경 영향 보고 방식을 구성합니다.
| 분류 | 개발 › 데이터·DB |
|---|---|
| 태그 | 분석검토개발자코드 |
---
name: data-lineage-agent
description: A skill for creating an agent to analyze data lineage and linkage across database scripts and stored procedures.
---
# Data Lineage Agent Skill
## Purpose
This skill assists in creating an agent that can analyze and report on the data lineage and linkage within a database system. It is ideal for understanding how changes to tables can affect the overall system and helps in uncovering the dependencies across different platforms.
## Steps to Create the Agent
1. **Access the Repository:**
- Link to the GitHub repository: [GitHub Repo](https://github.com/optuminsight-payer/COB-PARS_DB_SCRIPTS)
- Clone the repository to access all database scripts and stored procedures.
2. **Analyze Data Lineage:**
- Use tools to parse SQL scripts to identify table relationships and dependencies.
- Map out the data flow from source tables to final tables.
3. **Identify Changes Impact:**
- Implement logic to trace changes in intermediate tables to see which final tables are affected.
- Use graph databases or lineage analysis tools for better visualization and impact assessment.
4. **Host the Agent:**
- Choose a hosting platform (e.g., AWS, Azure) to deploy the agent for continuous analysis and reporting.
## Use Cases
- **Impact Analysis:** Determine the impact of changes in any table across the system.
- **Data Flow Mapping:** Visualize how data moves through the system from source to final tables.
- **Dependency Reporting:** Generate reports on table dependencies and affected platforms.
## Additional Features
- **Automated Alerts:** Notify users when potential impacts are detected.
- **Version Control Integration:** Link changes to specific commits in the repository for traceability.
## Example Variables
- `${repositoryUrl}`: The URL of the GitHub repository.
- `${platforms}`: List of platforms involved in the data flow.
This skill provides a structured approach to building an agent capable of comprehensive data lineage analysis, which can be crucial for database management and optimization tasks.어떤 프롬프트인가
데이터베이스 변경 영향과 의존성을 파악하는 에이전트를 설계할 때 쓰기 좋다. 저장소 접근, SQL 파싱, 계보 매핑, 호스팅까지 단계로 제시한다.
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