Data Analyst: Transforming Insights 📊
Senior Data Analyst | Business Intelligence Consultant
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I build AI agents & internal tools that act on data
Live GitHub Pulse — Broadcast Ticker for the Rive Broadcast & Livestream UI Challenge
I work as a data analyst and dashboard specialist, so when I saw this challenge, I didn't want to just animate something pretty — I wanted to see if I could bring actual live-data thinking into Rive, the same way I'd build a real-time analytics panel in my day job.
The concept: A broadcast-style lower-third ticker, similar to what you'd see on a live sports or esports stream — except instead of scores, it surfaces trending GitHub repositories in real time. Repo name, star count, and primary language, updating continuously like a stat panel during a live broadcast.
How it's built:
Data Binding — I set up a View Model (VMTicker) with three properties (repoName, starCount, language) and bound them directly to text layers on the canvas. Star count uses a Number-to-String converter so it renders cleanly as text.
Rive Scripting (Luau) — This is the part I'm most proud of. I wrote a custom script that runs inside the artboard and cycles through a set of trending repos every few seconds, pushing fresh values into the View Model through context:rootViewModel(). It's a small simulation of what a live API feed would do, built entirely with Rive's native scripting layer — no external app or backend needed.
State Machine animation — A looped timeline animates the accent bar's opacity in a subtle pulse, so the UI feels "alive" even during the seconds between data updates — like a live broadcast indicator light.
Why this approach: Most broadcast UI concepts lean heavily on motion and character work. I leaned into what I actually know — data pipelines and dashboards — and used Rive's newer Scripting and Data Binding features to bring that thinking into a motion-design tool for the first time. It was also my first time using Rive Scripting, so a good chunk of the build was debugging Luau type errors and figuring out the runtime API through trial and error.
https://editor.rive.app/file/live-github-pulse/2466722
https://www.linkedin.com/posts/abuaasif_rive-uidesign-datavisualization-ugcPost-7490354984044154881-mIL_/?utm_source=share&utm_medium=member_desktop&rcm=ACoAACRm5rcB0nVG0_HUX6-IXfuWqNGquZ-jMQU
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Project Overview
This is a personal portfolio and services site built for a working freelancer — myself — as part of the Make It Real Challenge. I'm a data visualization specialist and AI dashboard developer, and I wanted the site itself to reflect that work rather than just describe it. So instead of stock photography and generic copy, every visual on the site is a real screenshot from a project I've actually shipped.
The Concept
Most freelance portfolio sites lean on polished lifestyle photography — laptops on wooden desks, people in blazers looking thoughtfully at monitors. I wanted to flip that: let the actual product screens do the talking. The site is built around a simple idea — "solutions built on data, not guesswork" — and that shows up literally in the visuals, not just the copy.
What's on the site
Homepage: A direct hero statement ("I Turn Messy Data Into Decisions") backed immediately by a real dashboard screenshot from my Anomaly Review & Action Console, followed by a "recent work" section pulling in three separate real projects.
Services page: Four core offerings — Anomaly Detection Dashboards, Power BI & Data Analytics, AI-Integrated Internal Tools, and Custom Data Automation — each paired with an actual screenshot of that specific project (not a mockup).
About page: A short, direct bio and a real photo, no filler.
Contact page: A simple inquiry form paired with a data-visualization graphic that matches the site's overall theme.
How I used Finish Layer
Block Animations: I used on-appear and on-scroll triggers (Reveal and Slide styles) across the homepage, services, and contact pages. Section headings reveal as the page loads, and content blocks slide/fade in as the visitor scrolls — this turns what would be a static, all-at-once page into a guided, paced experience.
Block Transform: Rather than a flat grid, I applied a subtle rotation to a couple of key visuals (a dashboard screenshot and the contact-page graphic) — just a few degrees, enough to break the rigidity of the layout without sacrificing readability. It gives the page an asymmetrical, more intentional feel instead of looking templated.
Process
I built this using Squarespace's Blueprint AI to get a fast base structure, then went through every page replacing AI-generated placeholder content (stock imagery, generic service descriptions, an accidental product/ecommerce section) with real project data, real screenshots, and copy that actually reflects how I work with clients. The site is password-protected rather than published on a paid plan, and is fully responsive across desktop and mobile.
Access:
🔗 Site: https://pike-megalodon-4yb2.squarespace.com
(https://pike-megalodon-4yb2.squarespace.com)🔑 Password: Omega
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Superstore Sales Dashboard — 3-Page Power BI Report
Built an interactive 3-page Power BI dashboard using
the Superstore Sales dataset (9,994 orders across USA).
Page 1 — Sales Overview: KPI cards, monthly trend,
regional breakdown, category performance.
Page 2 — Product Performance: Top products, category
donut, profit analysis, sales vs profit scatter.
Page 3 — Customer & Shipping: Segment breakdown,
top 10 customers, monthly growth, ship mode distribution.
Tools: Power BI, DAX, Superstore Dataset
Theme: Dark professional with interactive year filter.
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Power BI Expert | Turning Raw Data into Actionable Insights
Power BI Expert | Turning Raw Data into Actionable Insights
Data Analytics Project | BlinkIT Grocery Sales Analysis
Excited to share my latest Data Analytics project ,where I analyzed BlinkIT Grocery Sales Data and delivery data to uncover meaningful business insights 📈
📊 What I worked on:
Analyzed sales performance across product categories, outlet types, sizes, and locations
Identified top-performing item categories and customer preferences
Studied the impact of outlet size, establishment year, and visibility on sales
Converted raw data into actionable insights and business recommendations
💡 Key Insights:
Fruits & Vegetables, Snack Foods, and Frozen Foods drive maximum sales
FOR FULL PROJECT VIST GIT HUB –( https://lnkd.in/d34sdAPz
)
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I’m excited to share my latest Data Analytics project where I analyzed Customer Shopping Behavior to uncover trends in sales, demographics, and purchasing habits.This project was a great exercise in building a complete data pipeline.
The Tech Stack:
Python (Pandas & NumPy): Used in Jupyter Notebooks for initial data exploration and statistical analysis.
PostgreSQL: Utilized for rigorous data cleaning, querying, and structuring the dataset for analysis.
Power BI: Built an interactive dashboard to visualize key metrics like seasonal trends, subscription impacts, and category performance.
Project Highlights:
✅ Data Cleaning: Leveraged PostgreSQL and Pandas to handle missing values and standardize categorical data.
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Venezuela’s Oil Reserves Analysis Dashboard 📊
I am excited to share my latest data analytics project focusing on the energy sector. Using a dataset covering 23 reservoirs, I designed a comprehensive dashboard to track production capacity and resource distribution in Venezuela.
Key Features: ✅ Real-time Metrics: Tracking the 390.50 Billion total barrels in reserve. ✅ Granular Analysis: Production capacity breakdown by reservoir name and oil grade (Extra Heavy to Light). ✅ Stakeholder Mapping: Visualizing the production sum by major operators.
Tools Used: [pandas(jupyter notebook)/mysql(for analysis and cleaning of data), Power BI / Excel(for building dashboard)]
I’d love to hear your thoughts or feedback on the dashboard design!
must visit my github for full project -( https://lnkd.in/dYKdZ8J2
)
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Data Analytics Project | BlinkIT Grocery Sales Analysis
Excited to share my latest Data Analytics project ,where I analyzed BlinkIT Grocery Sales Data and delivery data to uncover meaningful business insights 📈
📊 What I worked on:
Analyzed sales performance across product categories, outlet types, sizes, and locations
Identified top-performing item categories and customer preferences
Studied the impact of outlet size, establishment year, and visibility on sales
Converted raw data into actionable insights and business recommendations
💡 Key Insights:
Fruits & Vegetables, Snack Foods, and Frozen Foods drive maximum sales
Medium-sized outlets outperform others in overall revenue
FOR FULL PROJECT VIST GIT HUB –( https://lnkd.in/d34sdAPz
)
Feedback and suggestions are always welcome!
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Analytical, MIS and Expert in automating reports
Data Analyst & Power Platform Specialist
📍 Mumbai, India | 📞 +91 7021027927 | ✉️ maheshkheder329@gmail.com (mailto:maheshkheder199@gmail.com)
Analytical and results-driven Data & MIS Specialist with 5+ years of experience optimizing reporting frameworks, automating complex workflows, and designing business intelligence solutions in the financial and insurance sectors. Skilled in transforming raw data into actionable insights using Power BI, SQL, Advanced Excel (VBA), and Power Automate. Recognized for delivering end-to-end data pipelines, custom approval workflows, and robust financial models.
Core Capabilities & Technical Toolkit
Business Intelligence & Dashboards: Power BI (Expert DAX, Power Query, Dynamic RLS), SAP BO, Trend & P&L Analysis
Database & Data Architecture: SQL (Data Modeling, Query Optimization, Joins, Data Validation), Dataverse, SharePoint Lists
Process Automation: Excel VBA Macros, Power Automate (Multi-stage Approval Workflows, Data Integration)
Analytics : Data Cleaning, Data Reconciliation, Python (Data Processing & Visualization)
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Integrating modern automation into daily business operations serves as a catalyst for eliminating repetitive manual overhead, drastically reducing human error, and accelerating critical decision-making cycles. By leveraging structured workflows through tools like SQL, Excel VBA macros, Power BI dashboards, and custom Python automation scripts, organizations can transform complex, fragmented datasets into dynamic, real-time reporting systems. Rather than spending valuable hours manually aggregating reports, cleansing raw data, or cross-referencing records across disparate databases, automated pipelines seamlessly process and visualize key metrics in real time. This operational shift not only enhances operational speed and analytical precision across functions like MIS and performance tracking, but it also frees up core team members to focus on high-impact strategic initiatives and proactive business growth.
Name - Mahesh Narendra Khedekar
Contact No -(+91) 7021027927 [fast responce Conntact with whatapp]
Email ID - maheshkhedekar329@gmail.com
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Monthly Reinsurance Premium and Claim Register
The Monthly Reinsurance Premium and Claim Register is an advanced Excel-based reporting and administration engine tailored for insurance operations, treaty accounts, and claims management. Designed to handle high-volume bordereaux files, this solution automates premium allocations, cession calculations, and claims recovery tracking across complex reinsurance treaties.
By replacing manual spreadsheets with automated Power Query models, dynamic lookup formulas, and VBA macro pipelines, the system eliminates human calculation errors, prevents recovery leaks, and standardizes disparate insurance data streams into unified master logs. Key features include automated validation algorithms to flag cessions discrepancies, real-time tracking of paid versus pending claims, and interactive executive dashboards for audit readiness.
Whether processing proportional treaties, excess of loss accounts, or monthly bordereaux statements, this workflow cuts monthly closing timelines by up to 80%. It delivers complete, transparent data lineage, robust audit trails, and zero-error execution for finance, underwriting, and reinsurance operations teams.
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MS PowerBI certified DataAnalyst | Get results, improvements
MS PowerBI certified DataAnalyst | Get results, improvements
View more →
Data Analyst | Transforming raw data into clear insights.
Data Analyst | Transforming raw data into clear insights.
Data Specialist for Clean, Organized & Smart Reports
Data Specialist for Clean, Organized & Smart Reports
📊 Sales Tracking Dashboard | Excel + Power BI Project
Built an end-to-end interactive Sales Tracking Dashboard covering 2021–2024 across the entire US market.
Top-Line Numbers:
💰 Total Sales: $19,28,888
📈 Total Profit: $2,47,962
👥 Total Customers: 8,314 across all years
What the dashboard reveals:
🏆 Best-selling sub-categories: Phones ($2,79,464) and Chairs ($2,77,058) lead the pack — together accounting for nearly 29% of all sales
📅 Profit growth year-on-year:
→ 2021: $49,556 → 2022: $61,618 → 2023: $81,786 — consistent upward trajectory across Furniture, Office Supplies & Technology
🗺️ 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 — a clear signal for regional strategy review.
📦 Technology drives profit — highest-margin category across all 4 years, despite Furniture holding significant volume
🧾 Seasonal trends: Q4 is king — November ($2,34,013) and December ($2,41,464) are the strongest months. February dips to just $59,640 — opportunity for targeted campaigns.
👤 Top customer by profit: Tamara Chand at $8,981, followed by Raymond Buch ($6,939) and Sanjit Chand ($5,757)
Tools used: Microsoft Excel · Pivot Tables · Power Query · Charts & Slicers · Dashboard Design
This project sharpened my ability to turn raw transactional data into a clean, decision-ready visual — with filters for state, date, year, sub-category, and month.
Open to feedback! 👇
#Excel #DataAnalytics #SalesDashboard #DataVisualization #BusinessIntelligence #MicrosoftExcel #DashboardDesign
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🏦 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 — something they simply didn't have before.
What the data revealed:
✅ Net-positive portfolio: $435.8M disbursed, $473.1M recovered
⚠️ 13.8% bad loan rate = $28.25M net capital loss
📊 Debt consolidation drives nearly half of all loan applications
⏳ 73% of borrowers chose 60-month terms over 36-month
📍 60%+ of repayments concentrated in just 5 states (CA, NY, FL, TX, NJ)
Tools used: PostgreSQL → Excel → Power Query → Power BI + DAX
Built two interactive dashboards:
→ Summary: KPI cards, good vs. bad loan segmentation, loan status grid
→ 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 👇
#PowerBI #DataAnalytics #SQL #DAX #BankingAnalytics #PortfolioAnalysis #DataVisualization
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I Built a two-page Power BI dashboard on 190K+ FMCG transactions — 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 · DAX · Excel
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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 · DAX · PostgreSQL · Power Query
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