Design a data model for HR reporting and analytics

Help me design a data model for HR reporting and analytics in our data warehouse. Source systems: [HRIS, applicant tracking, payroll, performance, learning, benefits - e.g. "Workday, Greenhouse, ADP"] Data in scope: [headcount, hires, exits, compensation, performance, benefits, engagement] Questions it must answer: [e.g. "monthly headcount by department", "attrition by manager", "time to fill", "pay equity by level"] Tools: [warehouse, transformation tool, BI tool] Who will use it: [HR business partners, finance, executives, data scientists] Design for these HR-specific needs: - Effective dating: people change jobs, managers, departments, and pay over time. Use slowly changing dimensions or effective-dated snapshots so I can report "as of" any date. - Grain: define the grain of every fact table (e.g. one row per employee per month for headcount, one row per event for hires, exits, and promotions). - Org hierarchy: handle reorganizations and manager chains without breaking history. - Sensitive data: keep compensation, performance, health, and demographic data in restricted tables, with row- and column-level security and minimum group sizes so small groups can't be re-identified. - Definitions: one agreed definition each for headcount, FTE, attrition (voluntary, involuntary, regretted), and tenure. Return: 1. A star-schema outline: fact and dimension tables, grain, key columns, and keys. 2. A metric dictionary: Metric | Definition | Formula | Source table. 3. An access-control plan by user group. 4. Data quality checks to automate (e.g. duplicate employee IDs, missing managers, overlapping effective dates). 5. Build order: what to deliver first for quick value. Flag where privacy or employment law in [COUNTRY or REGION] may limit what we store or analyze, and tell me to confirm with legal or our data protection officer.