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PROJECT OVERVIEW

Steps
  1. 01PROJECT OVERVIEW
  2. 02DATASET REQUIREMENTS
  3. 03PROJECT ROADMAP
  4. 04STEP-BY-STEP IMPLEMENTATION
  5. 05EXPECTED OUTPUT AFTER EVERY MAJOR STEP — SUMMARY TABLE
  6. 06VISUALIZATION AND DASHBOARD
  7. 07INSIGHTS AND RECOMMENDATIONS
  8. 08FINAL PROJECT DELIVERABLES
  9. 09FURTHER READING & REFERENCES
  10. 10FINAL PROJECT CHECKLIST

PROJECT OVERVIEW

Project Title: Employee Attrition & HR Analytics Dashboard (Power BI)

Business Scenario: You are working as a Junior Data Analyst in the HR department of NorthStar Technologies, a mid-sized technology and consulting company with about 1,470 employees spread across three departments — Sales, Research & Development, and Human Resources. Over the last two years, the VP of HR has noticed that too many good employees are resigning, and replacing them is expensive (recruitment cost, onboarding time, lost productivity).

Company / Industry Context: NorthStar Technologies operates in a competitive talent market. Employees can easily move to competitors, so leadership wants to move from “gut-feeling” HR decisions to data-driven workforce decisions.

Business Problem: The HR leadership team does not have a single, reliable view of who is leaving, why they might be leaving, and which departments/roles are most at risk. Data currently sits in a static spreadsheet that nobody analyzes regularly.

Project Objective: Build a Power BI dashboard that shows attrition patterns across departments, job roles, income levels, overtime, tenure, and demographics — and translate those patterns into HR recommendations.

Key Stakeholders: - VP of Human Resources (main sponsor — wants the headline attrition rate and biggest risk drivers) - Department Managers (want to know attrition inside their own teams) - Talent Acquisition Team (wants to know where hiring effort should increase) - Finance (wants to understand attrition’s cost / income link)

Final Business Goal: Reduce voluntary attrition by helping HR target the right groups of employees with the right retention actions, instead of applying generic policies to everyone.

What Will the Student Finally Build?

  1. A cleaned, dashboard-ready HR dataset

  2. A documented data-cleaning process (Power Query steps)

  3. A Power BI data model with calculated columns and DAX measures

  4. A multi-page interactive Power BI dashboard with KPI cards, charts, filters and drill-through

  5. A set of written business insights (Finding → Insight → Business Impact → Recommendation)

  6. A short final presentation / summary report of findings

Tools used in this project: Microsoft Power BI Desktop, Excel/CSV (as the data source), Power Query, DAX.