Project Details

Led the development of a comprehensive Power BI dashboard for AtliQ Hardwares, a growing FMCG brand aiming to replace fragmented Excel reports with unified analytics. The project delivered a single, interactive report for Finance, Sales, Marketing, and Supply Chain teams. Built a robust data model with 10+ related tables, applied advanced Power Query transformations, and created dynamic DAX measures for KPIs like Net Profit, Forecast Accuracy, and Market Share. Designed intuitive navigation with drill-through, bookmarks, and dynamic filters for stakeholder-specific insights. Deployed reports to Power BI Service, ensured real-time data refresh, and incorporated stakeholder feedback for refinement. This project improved data visibility and decision-making while strengthening skills in data modeling, DAX, and enterprise reporting.

Project video

Project Details

Built a comprehensive Power BI dashboard for AtliQ Grands to address their revenue decline and market share challenges. The dashboard aggregates and visualizes key data from multiple properties, including revenue, occupancy, and cancellation rates. Key metrics such as ADR, RevPAR, and booking trends were tracked through 20+ dynamic DAX measures. The data model involved linking fact tables (Bookings, Aggregated Bookings) to dimension tables (Rooms, Hotels, Date) for optimized performance. The project also involved developing key insights, such as identifying the impact of cancellations on revenue and highlighting strategies to optimize elite room bookings and strengthen OTA partnerships. Gained proficiency in advanced DAX, building interactive visuals, and storytelling with data to drive actionable business decisions.

Project video

Project Details

This project simulates a real business scenario at AtliQ Hardware, a fictional computer hardware company facing delayed decision-making due to lack of timely insights. I solved 10 stakeholder-driven ad-hoc queries using MySQL, covering topics like YoY unique product growth (+36.33%), impact of COVID on sales, channel contribution (Retail: 73.22%), and customer discount analysis. I used complex SQL constructs (CTEs, joins, window functions) to extract actionable insights and built a Power BI dashboard for visualization. The final presentation mimics stakeholder reporting and showcases business storytelling, SQL acumen, and strategic thinking. This challenge was part of the Codebasics SQL Project series.

Project video

Project Details

This project was developed during my Data Analytics Internship at AtliQ Technologies (via Codebasics). I analyzed Wavecon Telecom’s performance before and after its 5G rollout across 15 Indian cities. Using Power BI and SQL, I explored revenue impact, customer churn, plan-level adoption, and competitor market share shifts. While the total revenue dropped by 0.5%, Tier-3 cities like Patna and Gurgaon showed strong gains, while metros like Delhi underperformed. I diagnosed key KPIs such as TAU, TUSU, ARPU, and evaluated which legacy plans failed vs. which new 5G plans gained traction. The dashboard and final presentation provided data-driven recommendations on product bundling, pricing, and retention campaigns.

Project video

Project Details

This internship project for Shield Insurance (via AtliQ Technologies & Codebasics) explored sales and customer engagement KPIs from Nov 2022–Apr 2023. Using Power BI and SQL, I developed a fully interactive dashboard that uncovers actionable insights across three views: Performance, Sales Mode, and Age Groups. Findings revealed February as the weakest month, Online mode’s volume-revenue gap, and key engagement patterns across age demographics. The dashboard provides clear strategic recommendations—ranging from upsell bundling to loyalty campaigns and churn mitigation. The project highlights my ability to translate raw insurance data into business insights that inform sales, marketing, and policy planning.

Project video

Project Details

AtliQ Mart, an FMCG manufacturer, was facing contract non-renewals due to late and incomplete deliveries. I built a supply chain dashboard using Microsoft Fabric and Power BI to track key metrics like OTIF, LIFR, and VOFR across cities, stores, and product categories. The analysis revealed major issues in Vadodara and stores like Coolblue. Using visual insights, I recommended SOP standardization, SKU-level interventions, and predictive logistics improvements. The dashboard enabled leadership to identify root causes, replicate best practices from top-performing stores like Propel Mart, and reduce service-level risks, improving client trust and fulfillment reliability.

Project video

Project Details

In fast-paced teams, important tasks often get lost in email threads. This project automates the process of extracting tasks from Outlook emails and tracking them in Notion. Using Zapier + AI, the system detects task emails, uses a structured prompt to extract task descriptions, assignees, and dates, and formats the content into line items. These tasks are then processed individually and added to a Notion database, ready for team execution. The project also includes an optional Excel lookup step to verify existing records or fetch metadata. Designed without any code, it boosts productivity and reduces repetitive admin work. Built during the Codebasics AI Productivity Challenge with guidance from mentors.

Project video

Project Details

I used to spend over an hour each day downloading CSVs from email, running SQL queries on our Postgres database, comparing the results line by line, and writing up a variance report manually. It was slow, repetitive, and easy to get wrong. So I built a complete automation using n8n and Gemini. The process starts with a Gmail trigger that extracts the CSV, pulls matching data from our system, and sends both datasets to a Gemini AI Agent. The AI compares row counts, totals, and city-level values, then generates a clear summary. That content is added to a Google Doc and sent back via email. Now, the entire task is fully automated and always consistent.

Project video

Project Details

I built a fully automated supply chain reporting system for a fictional FMCG brand, AtliQ Mart. The process begins with n8n, which extracts daily CSV data from 3PL emails and uploads it into a Supabase database. Quadratic AI is then used to clean and transform the data, generate fact tables, and calculate SCOR-aligned KPIs like OTIF %, Delivery Delays, Lead Time Variability, and Order Cycle Time. Using prompt-driven workflows, the system answers complex supply chain questions and creates stakeholder-ready insights. Power BI dashboards and slide decks are generated from these insights. This end-to-end automation replaces hours of daily manual work with a fast, reliable, AI-powered solution.

Project video

Project Details

Leave requests often involve back-and-forth emails, delays, and manual tracker updates. To solve this, I created an end-to-end automated approval system using Google Forms, Sheets, and n8n. Employees fill out a leave form, which logs into a Google Sheet. n8n detects the new row, formats a summary, and emails the manager with Approve/Reject buttons. When clicked, the request is updated in a centralized leave tracker sheet and a real-time status email is sent to the employee. No HR follow-ups, no spreadsheet edits, and complete audit logs. The process is fast, reliable, and easily adaptable for any team.

Project video

Project Details

Manual job searches waste time, miss roles, and fail ATS filters. This project automates job discovery using n8n and Google Gemini. Users enter a role like “Data Analyst”; Gemini suggests variations; JSearch API fetches listings; Gemini extracts keywords, recruiter comments, and matches projects from a CSV. Structured results auto-write into Google Sheets. The system reduces weekly job search time by 5–8 hours, improves resume targeting, and connects your experience to specific jobs. Ideal for career switchers, freshers, or anyone building a smarter portfolio. Fully no-code, API-driven, and AI-enhanced—ready for HRTech use cases.

Project video

Project Details

BizPro Solutions struggled with inefficient credit card usage: late fees, low reward utilization, and manual reporting. I built a 3-flow AI automation using n8n and Gemini AI that solves this. Flow 1 generates strategic recommendations; Flow 2 extracts metadata from PDFs; Flow 3 merges both into a structured report with actionable insights. Key components include auto PDF parsing, AI-powered card strategy, real-time Sheets updates, and Google Docs batchUpdate report creation. It flags risky behaviors, optimizes category-wise spend, and suggests card realignment. The solution automated 520+ statements, saving 8+ hours per employee monthly and unlocking ₹14–15L in financial opportunities annually. Designed as a scalable, repeatable workflow for any company.

Project video