Unlock Financial Insights Using Advanced SQL on Nifty 50 Data

Unlock Financial Insights Using Advanced SQL on Nifty 50 DataUnlock Financial Insights Using Advanced SQL on Nifty 50 Data

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Saransh Purohit

• 1d

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.

Data Analysis Data Engineering MySQL SQL

Yeasin Arafat

• Apr 10

This project simplifies personal finance by turning complex data into a clean, intuitive mobile experience. With smart spending insights, bill tracking, and real-time analytics, users can easily understand and manage their money. The result is higher engagement, better decision-making, and a more trustworthy financial product for everyday use.

Mobile Design Visual Design Web Design Adobe Photoshop Adobe XD Figma financeapp mobileapp userinterface

Rasel Alam Jubayed

pro

• Apr 11

Good work

NOMAN IJAZ

pro

• Apr 11

Your Money. On Autopilot.

Forget spreadsheets. Forget manual tracking. This platform thinks, moves, and grows your capital — while you sleep.

Figma Jitter uiuxdesign

MD AL AMIN

• Apr 11

This project demonstrates my ability to manage, organize, and process invoicing and billing data accurately using spreadsheet tools like Microsoft Excel and Google Sheets. The dataset includes 20 sample invoices generated over a three-month period, simulating real-world business transactions across multiple international clients.

Each record contains essential billing details such as invoice date, unique invoice number, client name, service description, quantity/hours worked, unit pricing, total amount calculation, and payment status (Paid, Pending, or Overdue).

The project highlights my skills in:

Accurate data entry and formatting

Invoice tracking and organization

Performing calculations (e.g., total amount = quantity × unit price)

Maintaining data consistency and structure

Handling financial records with attention to detail

This sample dataset reflects common tasks performed in data entry and billing roles, including managing client records, tracking payments, and ensuring data accuracy for financial reporting.