Edward Higson

Project Overview

Developed a comprehensive sales analytics dashboard for a major retail chain, providing real-time insights into sales performance, inventory management, and customer behavior patterns. The dashboard processes over 500,000 transactions daily and serves 50+ stakeholders across multiple departments.

Key Features

• Real-time sales performance tracking with automated alerts
• Advanced forecasting models using machine learning algorithms
• Interactive drill-down capabilities from region to store level
• Dynamic filtering by product category, time period, and geography
• Automated report generation and email distribution
• Mobile-responsive design for on-the-go access
• Integration with inventory management systems

Business Impact

The dashboard enabled the client to identify underperforming stores 40% faster, optimize inventory levels reducing waste by 25%, and improve sales forecasting accuracy by 35%. Monthly reporting time was reduced from 3 days to 30 minutes through automation.

Technologies Used

Project Overview

Created an executive-level KPI dashboard for a fast-growing SaaS company, tracking key metrics including customer acquisition, retention, lifetime value, and revenue growth. The dashboard provides actionable insights for C-level executives and department heads to make data-driven strategic decisions.

Key Features

• Comprehensive cohort analysis tracking customer behavior over time
• Real-time MRR (Monthly Recurring Revenue) tracking and forecasting
• Customer churn prediction models with early warning indicators
• Interactive cash flow analysis with scenario planning
• Automated budget vs. actual variance reporting
• Customer segmentation analysis with behavioral insights
• Integration with CRM, billing, and support systems

Business Impact

The dashboard helped the client reduce customer churn by 22% through early intervention strategies, improve cash flow forecasting accuracy by 45%, and identify high-value customer segments leading to a 30% increase in upselling success rates.

Technologies Used

Project Overview

Designed and implemented a robust ETL pipeline for a financial services firm, integrating data from multiple sources including legacy databases, Google Sheets, external APIs, and real-time transaction feeds. The pipeline processes over 2 million records daily and feeds into both Power BI and Tableau dashboards for different stakeholder groups.

Architecture Flow

Key Features

• Automated daily data extraction from 5 different source systems
• Real-time Google Sheets integration for manual data entry
• Data quality validation with automated error reporting
• Incremental loading to optimize performance
• Automated data lineage tracking and documentation
• Failure recovery mechanisms with email notifications
• Scalable architecture supporting 10x data volume growth

Business Impact

The ETL pipeline reduced manual data processing time from 8 hours to 30 minutes daily, improved data accuracy by 95%, and enabled real-time decision making. The automated system eliminated data silos and provided a single source of truth for all financial reporting.

Technologies Used