Ayaan khan

<p>Sales Insights Analysis for Q Hardware</p><p>Developed an end to end Business Intelligence solution for Q Hardware a mid sized consumer hardware and electronics distribution company operating across India through brick and mortar retail stores and ecommerce channels. The objective was to transform raw sales transactions into actionable insights that enabled data driven decision making for sales finance and executive leadership.</p><p>The project addressed key business challenges including inconsistent revenue reporting caused by multiple currencies limited visibility into profitability across customers markets and regions declining sales without clear root cause analysis and the inability to compare performance across sales channels. Stakeholders also lacked customer level profitability insights making pricing discounting and resource allocation difficult.</p><p>The solution was built using Power BI SQL Power Query DAX and Star Schema data modeling. SQL was used for data inspection validation cleaning and business analysis. Power Query handled data transformation and currency normalization by replacing raw sales values with normalized sales amounts. A Star Schema was implemented with a central Sales Transactions fact table linked to Customer Product Market and Date dimensions to improve reporting performance and simplify analysis. DAX measures were created for Total Revenue Sales Quantity Profit Margin Profit Contribution Percentage Customer Profitability and Year over Year growth.</p><p>An interactive Power BI dashboard was developed to provide insights across Revenue and Sales Trends Profitability Analysis Market and Zone Performance and Customer and Channel Performance. The dashboard included KPI cards trend analysis drill through functionality dynamic filtering contribution analysis and comparison visuals enabling stakeholders to quickly identify revenue drivers profitability gaps and underperforming regions.</p><p>The analysis revealed that high revenue markets were not always the most profitable and that a small number of customers and markets generated the majority of overall profit. Revenue decline was primarily driven by lower sales volume rather than pricing issues. Brick and mortar remained the dominant sales channel while ecommerce demonstrated growth potential. Profit contribution analysis helped prioritize high value markets and customers while profitability metrics supported better pricing and operational decisions.</p><p>The final solution delivered reliable revenue reporting improved profitability visibility automated KPI monitoring and faster decision making through interactive dashboards. It enabled leadership to identify high performing and underperforming markets optimize customer strategies and monitor business performance more effectively.</p><p>Technology Stack: Power BI Desktop Power Query SQL DAX Star Schema Data Modeling GitHub and PBIX.</p>