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This repository contains a comprehensive data analysis project focused on Time Series Forecasting and Statistical Anomaly Detection. The analysis tracks asset performance (specifically Close prices) over a multi-year period (2015–2021) to capture long-term growth trends, evaluate seasonal variance by month, and isolate periods of extreme market volatility.
By leveraging moving window techniques and statistical thresholds, this project successfully flags 69 key anomaly points where market behavior diverged significantly from historical averages.
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Designed a sleek modern Crypto App.
Clean and intuitive UI with real-time portfolio tracking, market charts, wallet management, quick buy/sell/exchange, and insightful analytics for crypto enthusiasts.
Nice 👍
Hi everyone! 👋
I'm new to @Contra, so I thought I'd introduce myself.
I'm Umaima Iqbal, a Computer Engineering student at UET Lahore with a strong interest in AI, automation, and web development.
I'm currently focused on learning by building real projects, improving my skills every day, and sharing my journey along the way.
Some of my recent offline AI automation projects include:
• Aura Sort
• Aura Chat
• Aura Sum
• Aura Extract
Each project is designed to work completely offline, with a focus on privacy, efficiency, and practical use cases.
I'm excited to connect with developers, creators, and professionals, learn from the community, and contribute through meaningful projects.
Looking forward to connecting with you all! :
Perfect
Project Title
Enterprise Financial Health & Risk Command Center
Project Overview
Engineered a comprehensive, interactive business intelligence dashboard using raw corporate financial datasets sourced from Kaggle. The goal of this project was to establish a centralized "Command Center" that bridges operational bottom-line metrics with enterprise balance sheet liabilities for high-level executive review.
The Technical & Analytical Process
Data Engineering & Preparation: Processed, extracted, cleaned, and structured unorganized raw financial logs to build a reliable data model mapping Net Income timelines against liability structures.
Interactive Risk Mapping: Designed custom action filters within a scatter plot framework. As shown in "Dashboard 1 (1).png", this allows stakeholders to actively select specific liquidity risk outliers on the Liquidity Risk Map (comparing Total Liabilities against Working Capital Ratio) to instantly filter and update corresponding multi-year Profitability Trends.
C-Suite Design Standards: Optimized the dashboard layout using a minimalist, corporate-friendly color palette (structured around graded blue-scale metrics for Net Income ranges from 20B to 28B) ensuring the visual assets meet strict presentation standards for executive board reviews.
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