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Manigandan Acharya
Data Specialist for Clean, Organized & Smart Reports
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Mumbai, India
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Mumbai, India
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π Sales Tracking Dashboard | Excel + Power BI Project Built an end-to-end interactive Sales Tracking Dashboard covering 2021β2024 across the entire US market. Top-Line Numbers: π° Total Sales: $19,28,888 π Total Profit: $2,47,962 π₯ Total Customers: 8,314 across all years What the dashboard reveals: π Best-selling sub-categories: Phones ($2,79,464) and Chairs ($2,77,058) lead the pack β together accounting for nearly 29% of all sales π Profit growth year-on-year: β 2021: $49,556 β 2022: $61,618 β 2023: $81,786 β consistent upward trajectory across Furniture, Office Supplies & Technology πΊοΈ Geographic concentration: California dominates at $3,90,145 in sales. New York ($2,46,517) and Texas ($1,51,436) follow. West Virginia sits at the bottom with just $536 β a clear signal for regional strategy review. π¦ Technology drives profit β highest-margin category across all 4 years, despite Furniture holding significant volume π§Ύ Seasonal trends: Q4 is king β November ($2,34,013) and December ($2,41,464) are the strongest months. February dips to just $59,640 β opportunity for targeted campaigns. π€ Top customer by profit: Tamara Chand at $8,981, followed by Raymond Buch ($6,939) and Sanjit Chand ($5,757) Tools used: Microsoft Excel Β· Pivot Tables Β· Power Query Β· Charts & Slicers Β· Dashboard Design This project sharpened my ability to turn raw transactional data into a clean, decision-ready visual β with filters for state, date, year, sub-category, and month. Open to feedback! π #Excel #DataAnalytics #SalesDashboard #DataVisualization #BusinessIntelligence #MicrosoftExcel #DashboardDesign
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π¦ Bank Loan Portfolio Analysis | Power BI Dashboard Project Analyzed 38,576 loan records across 50 states to give a bank's lending division a unified view of portfolio health β something they simply didn't have before. What the data revealed: β Net-positive portfolio: $435.8M disbursed, $473.1M recovered β οΈ 13.8% bad loan rate = $28.25M net capital loss π Debt consolidation drives nearly half of all loan applications β³ 73% of borrowers chose 60-month terms over 36-month π 60%+ of repayments concentrated in just 5 states (CA, NY, FL, TX, NJ) Tools used: PostgreSQL β Excel β Power Query β Power BI + DAX Built two interactive dashboards: β Summary: KPI cards, good vs. bad loan segmentation, loan status grid β Overview: Trends, geographic maps, term/purpose/employment breakdowns The next phase? Building a predictive risk scoring layer using DTI, interest rate, and employment length to flag at-risk loans before they default. Open to feedback from data folks in the community π #PowerBI #DataAnalytics #SQL #DAX #BankingAnalytics #PortfolioAnalysis #DataVisualization
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Every hospital generates thousands of data points daily but without the right lens, it's just noise. Built this Healthcare Analytics Dashboard to turn patient records into decisions. From tracking $1.4B in revenue across admission types to spotting a consistent dip in monthly billing trends the numbers tell a story most teams never get to read. The insight that stood out? Diabetes and Obesity quietly lead revenue by medical condition which says a lot about where healthcare demand is heading. This is what data visualization is actually for not prettier reports, but faster, clearer thinking. Tools: Power BI Β· DAX Β· PostgreSQL Β· Power Query
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I Built a two-page Power BI dashboard on 190K+ FMCG transactions β tracking revenue, SKU performance, promotional impact, and delivery across 3 channels and 3 regions. Uncovered a balanced 33% revenue split across all channels and identified the top 3 revenue-driving SKUs for smarter inventory decisions. Tools: Power BI Β· DAX Β· Excel
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