About this project

Dataset Description

The dataset integrates project management, scheduling, cost, and contractor data. It most likely comes from Primavera P6, ERP systems, and project control tools

Work Process

Here’s a high-level workflow for building this dashboard:

Data Collection

Extract project metadata, cost, and schedule data from: Primavera P6 (scheduling) ERP/Finance system (SAP/Oracle) Contractor reports Energization tracking logs

Data Transformation Clean and normalize channel names.

Standardize project IDs, contractor names, and status categories.
Calculate KPIs:
SPI = Earned Value ÷ Planned Value
CPI = Earned Value ÷ Actual Cost
Energization % = Energized ÷ Total
Create hierarchy: Department → Program → Project → Contractor.

Dashboard Development

Tool: Power BI (the style confirms it).
Page navigation built with buttons (Portfolio Overview, Regional View, etc.).
Visuals:
Donut & Bar for project breakdowns.
Heatmaps for department status.
KPI cards for top metrics.
Tables for detailed drill-downs.

Validation & Testing

Cross-check financial totals with accounting system. Validate SPI & CPI against P6 reports. Verify project status with PMO reports.

Deployment & Monitoring

Publish dashboard.
Dashboard refreshed monthly or weekly.
Used by PMO, executives, contractors, and regulators to track:
Delays & risks
Contractor performance
Schedule compliance (P6 usage)
Energization progress of Saudi power projects.
✅ Summary:
This PDC Portfolio Dashboard provides a 360° view of power projects. It integrates cost, schedule, and contractor performance into one system. The multi-page design supports executives (high-level KPIs), PMO (detailed tracking), and contractors (performance monitoring)

github

About this project

Dataset Description

The dataset represents regulatory inspection and compliance control data collected across multiple agencies and sites (SITESAGENCES), analyzed by DEX (regional/functional units).

Work Process

Here’s a high-level workflow for building this dashboard:

Data Collection

Collect inspection and compliance reports from regulatory systems.
Import data from field audits, internal quality checks, and agency logs.
Extract site-wise and DEX-wise control records..

Data Transformation

Clean and standardize site and DEX names.
Derive indicators:
Passage (Qualité) = Passed Controls ÷ Total Controls
Conformité Planning = On-Time Controls ÷ Planned Controls
Levées de Réserve % = Resolved Reserves ÷ Total Reserves
Create summary tables for “Top 5/10/15 sites”

Dashboard Development

Choose BI Tool Power BI.
Build interactive filters (Date, SITESAGENCES, DEX).
KPI Cards for quick indicators.
Pie/Bar charts for distribution by status.
Narrative “Summary Section” for management.

Validation & Testing

Cross-check with compliance officers.
Ensure reserve counts match inspection records.
Validate pass rate against official regulatory statistics.

Deployment & Monitoring

Dashboard published for compliance managers.
Updated regularly (weekly/monthly).
Used in regulatory review meetings to track performance and resolve critical issues.
✅ Summary:
This Regulatory Controls Monitoring Dashboard provides a real-time compliance overview. It consolidates quality, planning, and reserve resolution data at multiple levels (DEX, sites, agencies). Management can track inspection pass rates, planning adherence, and reserve closure progress, enabling data-driven regulatory compliance decisions.

github

About this project

Dataset Description

The dataset combines HR data (attrition, employees) and operational performance data (delivery & preparation work). It is likely sourced from HRIS (Human Resource Information Systems), Project Management Tools, and Operational Logs.

Work Process

Here’s a high-level workflow for building this dashboard:

Data Collection

HR data: Extract from HRIS system (e.g., SAP SuccessFactors, Workday).
Operations data: Extract from task/project management tools (Power BI).
Standardize into a single data warehouse (SQL, Excel, Power BI model).

Data Transformation Clean and normalize channel names.

Clean data (normalize roles, education, regions).
Create calculated fields:
Attrition Rate = Attrited ÷ Total Employees
Active Employees = Total – Attrited
Delivery Qty = Completed Deliverables
Blocker % = Blocked Deliveries ÷ Total Deliveries
Aggregate by Department, Region, Month, Job Role.

Dashboard Development

Tool: Power BI (given style and visuals).
Page 1 (Attrition Dashboard):
KPI cards, pie/bar charts for attrition by different factors.
Page 2 (Weekly Staff Performance):
KPI cards, monthly trends, blocker analysis, region-wise breakdown.

Validation & Testing

Cross-check with HR reports (headcount, attrition).
Verify delivery numbers with operational logs.
Validate blocker definitions with project managers.

Deployment

Publish dashboard for HR & Operations leadership.
Schedule weekly refresh for operational data, monthly refresh for HR data.
Used for decision-making on staffing needs, attrition reduction, and workload planning.
✅ Summary:
This combined dashboard provides a holistic view of workforce and operations. Page 1: Focuses on HR analytics (attrition, employee demographics).
Page 2: Focuses on operational performance (delivery, blockers, demand codes).
Together, they allow management to balance workforce capacity with business delivery performance.

github