Data Engineering Projects in Karachi CityData Engineering Projects in Karachi City
Projects
People
Cover image for I recently engineered a real-time
I recently engineered a real-time tracking system for a school to replace static reports with continuous feedback. Using a Google Sheets-to-Looker Studio pipeline, I automated the transition from raw teacher observations to parent-facing insights. Key Deliverables: Live Pipeline: Structured Sheets input for teachers to log 12+ data points per student daily. Grit Scoring Engine: Built custom logic weighting effort over mastery using cohort benchmarks. Dynamic URL Security: Implemented unique, filtered dashboard links for secure parent/student access. Automated Insights: Built-in trend indicators (Improving/Stable/Declining) for instant intervention. The Impact: The client now uses a live command center that eliminates manual reporting and provides real-time actionable intelligence.
0
145
Cover image for Multi-Drive Architecture: Synchronizing & Organizing
Multi-Drive Architecture: Synchronizing & Organizing 4 Enterprise Streams Project Overview: The client operated with four distinct Google Drives (Personal, Giant Ventures, WMBG Rentals, and Lock & Key Property Inspection) all linked under a single account. The data was heavily fragmented, with business assets, rental documents, and personal backups mixed across all platforms. I was hired to consolidate and structure this 100GB+ ecosystem into a unified, professional workspace. The Challenges: Cross-Drive Clutter: Files from different businesses were intermingled, causing massive confusion and slow retrieval. Storage Waste: High volume of redundant backups and temporary files taking up valuable cloud space. Syncing Issues: Inconsistent folder naming prevented smooth access across mobile and desktop devices. My Solution & Workflow: Unified Folder Hierarchy: Designed a master structure that separated the 4 entities while maintaining a logical link between them. Deep Data Sorting: Manually audited and moved over 100GB of files into their respective business or personal categories. The "Zero-Duplicate" Protocol: Identified and removed redundant files to optimize storage and reduce costs. Standardized Naming Convention: Established a consistent file-naming system for "Lock & Key" and "WMBG Rentals" to ensure future scalability. The Results: Turnaround Time: Completed the entire migration and organization within 3 days (ahead of schedule). Efficiency Boost: The client can now locate any document from any of the 4 drives in seconds. Seamless Sync: Guaranteed 100% folder accessibility across all client devices.
0
53
Cover image for QueryMind lets you query a
QueryMind lets you query a real database using plain English. Type a question, get an answer — no SQL knowledge needed. Built a production-grade AI agent using LangGraph that converts natural language to SQL, executes it on a real PostgreSQL database with 100,000+ rows, and automatically corrects errors in a retry loop if the query fails. Key features: 7-node LangGraph agent with conditional routing and self-correction pgvector semantic search for intelligent schema retrieval Full observability dashboard with real-time metrics and query history Trace replay — see every step the agent took to answer your question Deployed live: Next.js frontend on Vercel, FastAPI backend on Render Tech: LangGraph · Groq LLaMA 3.3 70B · PostgreSQL · pgvector · FastAPI · Next.js · Tailwind CSS Github: https://github.com/moiz-mansoori/QueryMind-NL2SQL-Agent-System
1
150