Data Requirements
Convert business requirements into comprehensive data specifications and governance rules
What You Can Do
You convert business process descriptions into structured data specifications that technical teams can implement without follow-up questions. The skill generates detailed data dictionaries specifying what data exists, how it flows, what quality standards it must meet, retention timelines, and compliance requirements. This bridges the communication gap between business stakeholders and data engineers, architects, and compliance officers.
Features
Defines core data entities and their properties with clear business semantics
Specifies how entities connect, including cardinality and dependency rules
Documents validation requirements, acceptable value ranges, and format constraints
Establishes data lifecycle rules aligned with regulatory and business needs
Traces data flow from source business processes through transformations
Defines ownership, access controls, and compliance requirements for each data element
Generates outputs that data engineers can use to build schemas and validation logic without clarification
Aligns data specifications with regulatory requirements (GDPR, HIPAA, SOX)
Example Output
Entity: Customer
- Attributes:
- customer_id (PK, UUID, Required, Immutable)
- email (String, Unique, Encrypted at rest)
- last_purchase_date (Date, Nullable, Updated daily)
- Relationships: 1:Many with Orders, 1:1 with Billing_Profile
- Quality Rules: Email must pass RFC 5322 validation; last_purchase_date cannot be future-dated
- Retention: 7 years after account closure per SOX compliance
Entity: Order
- Attributes:
- order_id (PK, Sequence, Required)
- customer_id (FK, Required, Indexed)
- order_total (Decimal 10,2, ≥0, Required)
- status (Enum: pending, confirmed, shipped, delivered, cancelled)
- Relationships: Many:1 with Customer, 1:Many with Order_Items
- Quality Rules: order_total must equal sum of Order_Items.item_price; status transitions follow workflow rules
- Retention: 3 years for transaction audit trail, 10 years for tax records
What's Included
- SKILL.md instruction file: Core prompting logic for data specification analysis
- Data Dictionary Template: Pre-structured format for entities, attributes, relationships, and governance rules
- Quality Rules Framework: Checklist for defining validation constraints, acceptable values, and format standards
- Compliance Mapping Worksheet: Cross-reference template linking data elements to regulatory requirements (GDPR, HIPAA, SOX)
- Retention Policy Calculator: Guidelines for determining data lifecycle based on business and legal retention needs
Who It's For
- Business Analysts — Define data specifications that bridge business and technical teams
- Data Engineers — Use precise specifications to build schemas, validation rules, and ETL pipelines
- Data Architects — Base detailed technical architecture on validated business requirements
- Compliance Officers — Audit data governance alignment with regulatory requirements
- Project Managers — Prevent scope creep and clarification delays by establishing clear data requirements upfront
Best For
- New system launches or migrations — Capturing comprehensive data requirements before development begins
- Cross-functional data disputes — Establishing single source of truth when teams disagree on what data is needed
- Compliance audits — Documenting data governance, retention, and quality standards for regulatory reviews
- Legacy system decommissioning — Mapping old data structures to new systems while preserving quality standards
- Data quality remediation — Identifying specification gaps that led to data issues
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