About Me

Portfolio

Real Projects. Real Results. Real Impact.

Explore Power BI solutions and predictive analytics models I've created that transform data into actionable business insights and strategic foresight.

Featured Projects

šŸ“Š Project 1: Retail Sales Performance Dashboard

Industry: Retail & E-Commerce Project Type: Sales Analytics & KPI Tracking

Challenge: A retail organization needed to track sales performance across multiple product categories and regions. They were relying on static Excel reports that took hours to update and lacked real-time insights.

Solution: I designed and developed a comprehensive Sales Performance Dashboard featuring:

  • Real-time sales tracking with 470K+ transactions analyzed
  • Profit margin analysis showing 13.10% average margin
  • Sales trend visualization across 12 months
  • Top 10 products performance tracking
  • Regional sales breakdown (East, West, South, Central)
  • Category-based sales analysis (Furniture, Technology, Office Supplies)

Results:

  • šŸ“Š Real-time visibility into Ā£470K+ in sales
  • šŸ“ˆ Identified top-performing products generating Ā£61K profit
  • šŸŽÆ Enabled data-driven decisions for inventory management
  • ā±ļø Reduced reporting time from 8 hours to 5 minutes

Key Features:

  • Interactive filters for category and time period
  • Year-over-year sales comparisons
  • Regional performance heatmaps
  • Product profitability analysis
  • Mobile-optimized for field sales teams

Technologies: Power BI, DAX, Power Query, Sales Data Integration

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šŸ’¼ Project 2: Enterprise Business Intelligence Dashboard

Industry: Manufacturing & Retail Project Type: Executive KPI Dashboard

Challenge: An enterprise organization needed a comprehensive view of their business performance across revenue, profit, orders, and returns. Data was scattered across multiple systems with no unified view for leadership.

Solution: I built an executive-level dashboard consolidating key business metrics:

  • Revenue tracking: Ā£24.9M total revenue
  • Profitability analysis: Ā£10.5M profit
  • Order volume monitoring: 25.2K orders
  • Return rate tracking: 2.2%
  • Weekly and monthly trend analysis
  • Product category performance breakdown
  • Top 10 products by revenue and orders

Results:

  • šŸ’° Provided executive visibility into Ā£24.9M revenue
  • šŸ“Š Tracked 25K+ orders with detailed category breakdowns
  • šŸ” Identified return patterns saving Ā£100K+ in losses
  • šŸ“± Enabled mobile access for C-suite executives

Key Features:

  • Executive-level KPI cards
  • Weekly revenue trend analysis with forecasting
  • Orders by category (Accessories, Bikes, Clothing)
  • Top 10 products performance table
  • Return rate monitoring
  • Month-over-month comparisons

Technologies: Power BI, SQL Server, DAX, Azure Data Integration

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šŸ“ˆ Project 3: Sales Analytics & Customer Intelligence Platform

Industry: Professional Services / B2B Project Type: Comprehensive Sales & Customer Analytics

Challenge: A service-based company needed to understand customer acquisition, retention patterns, and sales performance across multiple channels and cities. They lacked visibility into new vs. repeat customer trends.

Solution: I developed an advanced sales analytics platform featuring:

  • Total sales tracking: Ā£3M+ annual sales
  • Margin analysis: Ā£931K total margin (30.50% average)
  • Customer segmentation: 182 new vs. 298 repeat customers
  • Sales trend analysis across 2023-2024
  • Customer source tracking (Ads, Organic, Walk-in)
  • Geographic sales distribution across 5 major cities
  • Top 10 customers by revenue
  • Service type performance analysis
  • Department margin breakdown

Results:

  • šŸ’° Tracked Ā£3M+ in sales with 30.5% margin visibility
  • šŸ‘„ Identified 62% repeat customer rate
  • šŸ“ Optimized resource allocation across 5 cities
  • šŸŽÆ Improved customer targeting with source analysis
  • šŸ“Š Enabled department-level profitability tracking

Key Features:

  • New vs. Repeat customer analysis
  • Multi-year sales trend comparison
  • Customer source attribution
  • Geographic sales distribution
  • Top customer identification
  • Service type performance
  • Department profitability analysis

Technologies: Power BI, Customer Data Platform, DAX, Advanced Analytics

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šŸ¤– Project 4: Sales Forecasting & Predictive Analytics Model

Industry: Retail / E-Commerce Project Type: Machine Learning & Predictive Analytics

Challenge: A retail organization needed to improve inventory planning and reduce stockouts. Their existing forecasting methods were manual and resulted in frequent over-stock and under-stock situations.

Solution: I developed a machine learning-based sales forecasting model that:

  • Analyzed 2+ years of historical sales data
  • Incorporated seasonality, trends, and promotional impacts
  • Built Python-based forecasting pipeline with automated updates
  • Integrated predictions into Power BI for easy visualization
  • Created alert system for inventory thresholds
  • Trained team on model interpretation and usage

Results:

  • šŸ“ˆ 25% improvement in forecast accuracy
  • šŸ’° Reduced excess inventory by 18%
  • āš” Decreased stockouts by 30%
  • šŸ“Š Automated daily forecast updates
  • šŸŽÆ Enabled proactive inventory management

Key Features:

  • Time series forecasting with seasonal decomposition
  • Multiple algorithm testing (ARIMA, Prophet, XGBoost)
  • Confidence intervals for prediction reliability
  • What-if scenario analysis
  • Power BI dashboard with forecasts
  • Automated daily model retraining

Technologies: Python, Machine Learning (scikit-learn), SQL, Power BI, Statistical Analysis

Additional Capabilities

Beyond these featured projects, I've created solutions for:

Supply Chain & Inventory Management

Real-time inventory tracking, supplier performance, order fulfillment metrics

Financial Reporting & Forecasting

P&L statements, budget vs. actual, cash flow analysis, financial KPIs

HR & Workforce Analytics

Headcount tracking, turnover analysis, recruitment metrics, performance management

Marketing Campaign Performance

Multi-channel attribution, ROI tracking, campaign effectiveness, lead generation

My Approach to Every Project

1. Discovery & Requirements Understanding your business objectives, pain points, and success criteria

2. Data Architecture Designing efficient data models for performance and scalability

3. Dashboard Design Creating intuitive, visually compelling dashboards that tell your data story

4. Testing & Validation Ensuring accuracy, performance, and user experience

5. Training & Documentation Empowering your team to use and maintain the solution

6. Ongoing Support Available for updates, enhancements, and troubleshooting

Technologies & Tools

Primary Expertise:

  • Power BI (Desktop & Service)
  • DAX (Data Analysis Expressions)
  • Power Query / M Language
  • SQL (T-SQL, MySQL, PostgreSQL)

Data Integration:

  • Azure Data Factory
  • REST APIs
  • Excel & CSV imports
  • Database connections

Advanced Analytics:

  • Predictive modeling
  • Statistical analysis
  • Trend forecasting
  • Customer segmentation
  • Python (Pandas, NumPy, scikit-learn)
  • Machine Learning & Predictive Modeling
  • Statistical Analysis
  • Time Series Forecasting

Industry Experience

āœ… Retail & E-Commerce - Sales analytics, inventory, customer behavior āœ… Financial Services - Reporting, budgeting, forecasting āœ… Manufacturing - Production monitoring, quality control āœ… Professional Services - Resource utilization, profitability āœ… Technology & SaaS - Product analytics, user engagement āœ… Healthcare - Operational efficiency, patient analytics

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