📊 Workforce Insights Dashboard

Tableau | Data Modeling | Analytics Engineering | Business Intelligence

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Overview

The Workforce Insights Dashboard is a production-style business intelligence solution designed to provide leadership and operational teams with a single source of truth for workforce performance, attrition risk, and hiring efficiency.

This project demonstrates end-to-end analytics engineering, from structured data modeling and validation to interactive dashboard development and stakeholder-ready reporting.

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📊 Workforce Analytics Solution Architecture

┌───────────────────────────────────────────┐
│ Raw Workforce Data Sources                 │
│ (CSV / Excel / Database)                   │
└─────────────────────┬─────────────────────┘
                      ▼
┌───────────────────────────────────────────┐
│ Data Cleaning & Validation                 │
│ (Python / SQL)                             │
└─────────────────────┬─────────────────────┘
                      ▼
┌───────────────────────────────────────────┐
│ Analytics Data Model                       │
│ (Star Schema / Logical Layer)              │
└─────────────────────┬─────────────────────┘
                      ▼
┌───────────────────────────────────────────┐
│ Tableau Workbook (.twb)                    │
└─────────────────────┬─────────────────────┘
                      ▼
┌───────────────────────────────────────────┐
│ Interactive Dashboards & KPI Views         │
└───────────────────────────────────────────┘

Key Features

Executive KPI View

• Headcount trends
• Attrition and retention rates
• Hiring velocity and time-to-fill

Operational Analytics

• Department-level performance benchmarking
• Regional workforce distribution
• Role-based productivity analysis

Drill-Down Capabilities

• Filter by department, region, role, and time
• Employee lifecycle tracking from hire to exit

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Data Model

The dashboard is powered by a clean analytics layer using a star schema design.

Fact Table

fact_workforce_metrics

• employee_id
• date_id
• performance_score
• attrition_flag
• hire_date
• exit_date
• time_to_fill

Dimension Tables

• dim_employee
• dim_department
• dim_region
• dim_role
• dim_date

This structure enables high-performance filtering, scalable reporting, and consistent metric definitions across stakeholders.

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Data Quality & Validation

The pipeline enforces:

• Schema validation (null checks, type enforcement)
• Duplicate detection on primary keys
• Range checks on performance and date fields
• Consistency checks between fact and dimension tables

Any invalid records are flagged before dashboard refresh to ensure high data integrity and reporting reliability.

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