Freelancers using SQL in Noida
Freelancers using SQL in Noida
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Aditya Tanwar
Faridabad, India
Data Insights & Dashboards Curated for Success
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Data Insights & Dashboards Curated for Success
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Coffee Shop Sales Analysis
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39
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Real Estate Sales and Distribution Analysis
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19
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British Airways Reviews Analysis
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19
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SQL
(3)
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Saransh Purohit
Delhi, India
Data Analyst | SQL & Power BI Specialist
New to Contra
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Data Analyst | SQL & Power BI Specialist
1
In this technical deep-dive, I engineered a robust SQL script to extract high-level financial insights from 20+ years of Nifty 50 data. I moved beyond basic queries to implement complex analytical functions that simulate real-world market tracking. Market Sentiment Logic: Developed a CASE-based classifier to identify Bullish/Bearish trends using 50-day Moving Averages. Volatility & Risk: Calculated day-on-day price fluctuations and ranked high-risk trading days. Momentum Tracking: Integrated window functions (LAG/LEAD) to compute RSI-base logic and 30-day price momentum. Efficiency Metrics: Analyzed Turnover Efficiency to understand market liquidity during peak trading hours. This project demonstrates my ability to handle large-scale financial datasets and translate raw numbers into strategic market indicators.
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Risk management analysis
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Developed a comprehensive Stock Market Analysis tool using SQL and Power BI to visualize Nifty 50 data. Data Processing: Cleaned and transformed raw financial datasets using Excel and SQL queries. Interactive Visuals: Built 3 dynamic dashboards tracking price trends, volatility, and sectoral rotations. Business Insights: Identified key market drivers and risk factors through historical data analysis. Financial Expertise: Proven experience in stock market data analysis (Nifty 50). Tech Stack: Power BI, SQL, Microsoft Excel.
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106
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Nifty 50 Stock Market Analysis
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3
SQL
(4)
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Ritik Goyal
Delhi, India
Python & Django developer for web apps and APIs
New to Contra
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Python & Django developer for web apps and APIs
1
Built a Python-powered automated trading tool that pulls live market data, runs technical analysis, and generates real-time trade signals. Features normalized comparison charts across multiple assets (Nifty, USD Index, Brent Crude, US 10Y Yield), a macro pressure table, correlation analysis, and a portfolio helper. Backend built in Python with automated data pipelines, live market feeds, and signal interpretation logic that flags bullish/bearish pressure. Clean, data-dense dashboard for fast decision-making. Tech: Python, Pandas, REST APIs, data automation, real-time charting.
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Hit a classic Django trap this week and figured it's worth sharing since so many people are running into it now. I was adding an LLM feature to a Django app. The AI call takes a few seconds, so naturally I made the view async so it doesn't block a worker while waiting. Wrote the async view, called the ORM like I always do, and boom: SynchronousOnlyOperation: You cannot call this from an async context. Turns out Django's ORM can't just be called normally inside async code. The classic sync API isn't safe in an event loop, so Django protects it and throws this error instead. The fix is simpler than most people think. Since Django 4.1 the ORM has async versions of everything, same names with an "a" prefix. So objects.get() becomes await objects.aget(), create() becomes acreate(), save() becomes asave(). For loops over querysets, async for works directly. And for old sync code or third party libraries you can't change, wrap them with sync_to_async(). Why this matters right now: everyone is bolting AI features onto Django apps, and LLM calls are exactly the slow I/O that async is made for. Which means a lot of devs who never touched async Django are suddenly hitting this error for the first time. One honest caveat: transactions still don't fully work in async mode, so if you need atomic blocks, keep that path sync and wrap it. Anyone else made the jump to async views yet, or still happily on WSGI?
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An AI-driven trading engine that analyzes 200-DMA breakouts and real-time market sentiment to generate long/short recommendations. It scans 1,500+ NSE stocks in under 2 seconds and uses generative AI to build option strategies, delivering event-driven trade signals end-to-end. I built the full Django backend, async APIs, and the signal-generation logic. Accomplishments and responsibilities: Built an AI-driven trading engine analyzing 200-DMA breakouts and market sentiment, generating long/short signals with ~70% directional accuracy — outperforming baseline strategies by 35%; Integrated generative-AI insights for automated option-strategy creation (spreads, straddles, condors), improving Sharpe ratio by 1.6× and cutting manual analysis time by 60%; Developed a Django backend with async APIs scanning 1,500+ NSE stocks in under 2 seconds, achieving 40% lower latency with event-driven alerts.
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An AI-powered news platform that delivers concise, real-time AI-industry updates to 2,500+ active users. It scrapes and aggregates 500+ sources daily, removes duplicates, and uses generative-AI summarization to cut reading time significantly while surfacing the most relevant stories. I built the backend responsible for scraping, deduplication, and the LLM summarization pipeline.
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74
SQL
(1)
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Vikas Kashyap
Delhi, India
Data visualization engineer, Data Analyst, BI Expert
11
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Data visualization engineer, Data Analyst, BI Expert
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Power BI Dashboard for Full-Body Alignment Assessment
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5
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Executive Summary Dashboard for Google Merchandise Store
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13
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National Accident Statistics Dashboard in Google Looker Studio: I built an interactive Looker Studio dashboard using Google Sheets as the data source to visualize national accident statistics. The report analyzes accidents by region, time, severity, and demographics. A scheduled data re:fresh every 15 minutes keeps the dashboard updated in real time. As a Data Visualization Expert, I combined automation and design to deliver a clean, insightful, and dynamic Looker Studio dashboard for data-driven decision-making. 🎉 💯 🎉
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156
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Ecommerce Analytics Dashboard in Looker Studio
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5
SQL
(1)
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Kavin Sharma
Dadri, India
Expert & Passionate Fullstack Engineer 8+ Years Experience
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Expert & Passionate Fullstack Engineer 8+ Years Experience
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HR Job recruitment Web Applications
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19
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Lambdax.ai
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22
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Hospital Management System
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28
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Insurance Web Applications
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15
SQL
(1)
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Yash Saini
Delhi, India
Full-Stack Developer (Angular • .NET • React Native)
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Full-Stack Developer (Angular • .NET • React Native)
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Legacy .NET Modernization & SQL Optimization Stop the lag. I migrate legacy ASP.NET (http://ASP.NET) WebForms to .NET 8 Core with zero downtime. I specialize in handling lakhs of data rows through advanced server-side pagination, SQL profiling, and index tuning. What you get: ✅ .NET 8 Migration Roadmap ✅ 100k+ Row Data Optimization ✅ Zero-Downtime Deployment ✅ Performance Audit #DotNet #SoftwareArchitecture #LegacyModernization #SQLServer #FullStackDeveloper #BackendEngineering #FreelanceDeveloper #ZeroDowntime #DatabaseOptimization
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ASP.NET (http://ASP.NET) + SQL Server e-commerce: dynamic listings, server-side pagination, fast search, and robust cart. Stored procs tuned for speed. Want enterprise-grade performance? I can help.
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React Native (Expo) + Firebase video app: subscriptions/PPV, creator pages, secure uploads, and push notifications. TypeScript, Cloud Functions, and Stripe-ready. Looking to launch fast? Ping me.
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IoT dashboard (React): live charts, alerts, and device telemetry. API integration, caching, and graceful fallbacks. Clear UX, zero fluff—data that moves. Need real-time visibility? DM me.
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50
SQL
(2)
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Urvi Walia
Delhi, India
Transforming data into insights that drive growth with AI
New to Contra
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Transforming data into insights that drive growth with AI
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Sales Analysis Dashboard Project Built an interactive Sales Analysis dashboard to track revenue, sales trends, product performance, and customer purchasing behavior. Analyzed sales data to identify growth opportunities and support data-driven business decisions. Key Insights: Identified top-performing products and sales regions Analyzed monthly sales trends and customer buying patterns Tracked KPIs to improve sales performance and forecasting Skills Used: Data Analysis • KPI Reporting • Data Visualization • Dashboard Development • Business Intelligence Tools: Power BI • Excel • SQL • Python
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Customer Segmentation Case Study Analyzed customer purchasing behavior using data analysis techniques to identify high-value customer segments and buying patterns. Cleaned and processed raw customer data using Excel and Python, then created interactive dashboards in Power BI to visualize customer demographics, spending habits, and retention trends. Key Business Improvements & Decisions: Identified the most profitable customer groups for targeted marketing Helped optimize marketing campaigns based on customer behavior Suggested personalized offers for high-value customers to improve retention Reduced unnecessary marketing spend by focusing on the right audience segments Improved decision-making through clear KPI dashboards and customer insights Tools Used: Excel • Python • SQL • Power BI
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IT Service Management Dashboard Project Developed an interactive IT Service Management dashboard to monitor ticket volume, incident trends, SLA performance, and support team efficiency. Analyzed operational support data to identify service bottlenecks, improve response times, and support data-driven operational decisions. Key Business Insights & Decisions: Monitored ticket creation and closure trends to improve operational efficiency Identified high-priority and high-severity incidents requiring immediate attention Tracked SLA compliance rates to reduce delayed ticket resolutions Analyzed support categories and work types to optimize resource allocation Evaluated top-performing IT agents based on ticket resolution performance Improved service quality monitoring through customer satisfaction analysis Dashboard Highlights: Ticket Volume & Closure Tracking SLA Performance Monitoring Ticket Priority & Severity Analysis Support Category Breakdown IT Agent Performance Analysis Customer Satisfaction Metrics Interactive Filters for Dynamic Reporting Skills Used: Data Cleaning & Transformation Exploratory Data Analysis (EDA) KPI Monitoring & Reporting Operational Data Analysis Data Visualization Dashboard Development Business Intelligence Reporting Insight-Driven Decision Making Tools & Technologies: Power BI • Excel • SQL • Python • DAX • Data Visualization
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Tesla Sales & Market Analysis Project Conducted a data-driven analysis of Tesla’s sales performance, market trends, and customer demand patterns using real-world datasets. Cleaned and analyzed large datasets to identify revenue trends, regional performance, and key business insights that could support strategic decision-making. Key Business Insights & Decisions: Identified top-performing sales regions and revenue-driving markets Analyzed customer demand trends to understand purchasing behavior Detected seasonal sales patterns to support forecasting strategies Helped highlight opportunities for improving sales performance and market targeting Built interactive dashboards for easy tracking of KPIs and business metrics Skills Used: Data Cleaning & Preprocessing Exploratory Data Analysis (EDA) Sales Trend Analysis Data Visualization Dashboard Development Business Intelligence Reporting KPI Analysis Business Insight Generation Tools & Technologies: Excel • Python • SQL • Power BI • Pandas • Matplotlib
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SQL
(2)
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Himanshu Narwal
Delhi, India
Transforming complexity into clarity through data.
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Transforming complexity into clarity through data.
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Utilise SQL to retrieve data from datasets
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15
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Winning space race with data science
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26
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Compare machine learning classification algorithms
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13
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Develop a responsive Python dashboard
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15
SQL
(2)
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