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🟨 Power BI Project Guide

HCC Analytics BD

This folder is the approved location for Power BI project assets built from the Bangladesh HR Compensation & Compliance Analytics dataset.

Use it to create management-ready dashboards for workforce, payroll, attendance, benefits, pay equity and compliance monitoring—without exposing real employee or company data.

📘 For the full use-case, page-design and implementation guide, read POWER_BI_USAGE_GUIDE.md.

🚀 Best ways to use this Power BI project

Use case Best audience Primary outcome
Executive HR overview Management, HR Head Headcount, payroll cost, attendance and compliance at a glance
Payroll cost control HR Operations, Finance Gross pay, net pay, overtime, deductions and monthly variance
Attendance monitoring HR Operations, Line Managers Absence, lateness, leave and working-hours exceptions
Compensation review HR, Finance, Leadership Grade, department, gender and location pay comparisons
Benefits coverage HR, Rewards Team PF, insurance, medical, transport and meal enrolment gaps
Compliance tracking HR Compliance, Audit Open exceptions, risk levels, owners, due dates and closure status
Portfolio and training Learners, Analysts, Recruiters Power Query, star schema, DAX, visual storytelling and HR analytics practice

🧭 Where it can be used

  • HR monthly review meetings
  • Management and board presentations
  • Payroll and finance reconciliation
  • Department manpower-cost analysis
  • Internal audit and compliance follow-up
  • Compensation and pay-equity studies
  • HR analytics training, GitHub and portfolio projects
  • Scenario-based interview or assessment demonstrations

⚡ Quick start

  1. Download or clone the repository.
  2. Open Power BI Desktop.
  3. Select Get Data → Text/CSV and import the required files from data/.
  4. Use employees as the main employee dimension.
  5. Create one-to-many relationships using Employee_ID.
  6. Add a calendar table for payroll, attendance and compliance trend analysis.
  7. Copy the recommended measures from ../bi/power_bi_dax_measures.md.
  8. Build pages using the blueprint in POWER_BI_USAGE_GUIDE.md.
  9. Refresh, validate totals and remove all credentials before sharing.

Recommended source model: ../bi/data_model_and_setup.md

🗂️ Recommended report pages

  1. Executive Overview — headcount, payroll, attendance and compliance
  2. Workforce Profile — department, grade, location, gender and employment type
  3. Payroll & Overtime — gross pay, net pay, OT cost, deductions and variance
  4. Attendance & Leave — attendance rate, absence, lateness, leave and working hours
  5. Benefits Coverage — eligibility, enrolment and benefit gaps
  6. Pay Equity — gender, grade and department compensation comparison
  7. Compliance & Risk — exception status, risk level, owner, due date and closure tracking
  8. Employee Drill-through — one synthetic employee’s consolidated record

📦 Recommended project format

For a normal Power BI Desktop file:

HCC_Analytics_BD.pbix

For source-controlled development, prefer a Power BI Project when available:

HCC_Analytics_BD.pbip

A .pbip project is easier to inspect, compare and review because more of its structure is stored as text rather than one large binary file.

⬆️ Upload method

Standard-size PBIX

  1. Refresh using only the synthetic files from data/.
  2. Confirm all visuals and measures reconcile with the source files.
  3. Remove credentials, local paths and unused connections.
  4. Save the reviewed file as HCC_Analytics_BD.pbix.
  5. Upload it into this powerbi/ folder.

Large PBIX

Use Git LFS or attach the PBIX as a GitHub Release asset rather than adding a large binary repeatedly to normal Git history.

🔐 Mandatory security review before upload

  • ✅ Confirm all data is synthetic or properly anonymised.
  • ✅ Remove cached credentials, API keys, database passwords and private endpoints.
  • ✅ Replace personal local paths with parameters or documented relative paths.
  • ✅ Review Data source settings and clear permissions where appropriate.
  • ✅ Remove unused queries, hidden tables and unnecessary columns.
  • ✅ Inspect Power Query parameters and M code for secrets.
  • ✅ Confirm external custom visuals and connectors are trusted.
  • ✅ Review and test Row-Level Security roles when included.
  • ✅ Remove private gateway or automatic-refresh dependencies.
  • ✅ Scan the file with endpoint security before publishing.

⚠️ Responsible-use boundary

This is a synthetic learning and decision-support project. It is not a substitute for legal, payroll, tax or compliance advice.

Before real organisational use, validate:

  • current wage gazettes and sector rules;
  • applicable Bangladesh labour requirements;
  • tax-year and payroll rules;
  • company policies and collective agreements;
  • data privacy, access and retention requirements.

🔗 Related files

Prepared by: Musa
Project: HCC Analytics BD
Data type: Fully synthetic demo data