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Shopify + Etsy + Ad Spend — Turning Raw Exports Into a Profitability Picture
Client sold on Shopify and Etsy, ran ads on Facebook and Google, had no idea if she was profitable. 4 pages of raw, disconnected data came in. 2 days later: net revenue after returns, total ad spend across both platforms, and which products actually made money — 11 clean, connected pages.
The hardest part wasn't the math — it was getting the data to agree with itself. Mixed date formats, ad platforms reporting on different schedules, No shared key between sales and ad spend. All of it had to be standardized before a single number could be trusted.
I don't charge a fixed price — I work within the client's budget and what the project's actually worth.
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This portfolio sample shows how I evaluate AI agents and automated workflows to find reliability problems, broken logic, and weak edge-case handling. I review whether the system completes the intended task, uses tools correctly, follows instructions, handles ambiguity, and produces an output that can actually be trusted.
The work focuses on identifying failure points before they become real user problems, including incomplete task execution, incorrect assumptions, workflow dead ends, hallucinations, and verification gaps. This is a portfolio demonstration of my AI agent evaluation and red-teaming work. No confidential client information is included.
Thorough breakdown! Robust edge-case handling and reliability checks are definitely the trickiest part of building reliable AI agents 🤖📊
This might be the project that took the most time and effort to bring to a final finish line, but the result is truly worth it.
I am thrilled and excited to share with you OmniPulse Analytics Hub, an end-to-end Business Intelligence project I’ve been working on.
The idea wasn't just about putting a few charts together; the real challenge was deep in the backend and setting up a solid data model: linking 18 tables, building a proper Star Schema, and writing custom DAX measures to deliver accurate, error-free KPIs.
In this project, I focused on:
• Professional data cleaning and preprocessing.
• Table relationships and implementing Time-Intelligence using a dedicated DimDate table.
• Developing advanced DAX measures to analyze sales trends, return rates, and inventory levels.
• Designing a clean and intuitive user interface enabling management to read the numbers and make instant decisions.
• Integrating a one-click Executive Summary providing a complete project overview, key metrics, and dashboard status for immediate decision-making.
The dashboard features two main sections:
📌 Executive Overview (Comprehensive view of revenue, total sales, and overall performance rates)
📌 Category & Sales Breakdown (In-depth category analysis and low-stock tracking)
The biggest takeaway from working on this project: A massive amount of disorganized data is worthless. The true art lies in turning a mess of numbers into a clear, actionable story.
I'd love to hear your thoughts and welcome any feedback or suggestions! 👇
#PowerBI #DataAnalytics #BusinessIntelligence #PowerQuery #DAX #DashboardDesign #DataVisualization #DataModeling #Retail #DataScience
