Portfolio - Rita Mahato

Hello, I am

Rita Mahato

Data Analyst

About Me.

Bridge the gap between raw data and boardroom strategy by crafting clear, actionable insights that enhance performance and accelerate decision-making. Experienced in SQL, Excel, Power BI, and Python, with strong capabilities in KPI framework design, dashboard strategy, trend analysis, and business performance reporting.

Microsoft Certified Power BI Data Analyst specializing in architecting high-performance data models and advanced DAX calculations to drive strategic business intelligence solutions.

Strengthened data analytics skills by leveraging YouTube Studio to monitor key performance indicators (Watch Time, CTR, Subscriber growth), enabling the identification of actionable growth drivers.

Ranked Top 20 out of 2090 participants (Top 1%) in the Codebasics Resume Project Challenge.

Seeking impact-driven Data Analyst / Business Analyst roles supporting strategic decision leadership.

1

Excel Project

5

PowerBI Projects

1

SQL Project

1

Python Project

Skills.

SQL

Python

Power BI

Data Modeling

Stakeholder Management

Problem Solving

Effective Communication

Projects.

My Experience.

Virtual Data Analyst Intern — AtliQ Technologies Oct 2025 – Present

Analyzed datasets using SQL and Power BI to identify trends, revenue patterns, and operational gaps.
Built high-performance dashboards with star-schema modeling, DAX measures, and optimization using DAX Studio.
Designed ETL workflows with Power Query, ensuring clean, reliable, and well-structured datasets.
Created project documentation including methodologies, transformations, and insights.
Collaborated with mentors and cross-functional teams to deliver analytics aligned with business goals.

YouTube Channel Analytics — Independent Project Aug 2019 – Jul 2024

Uploaded 40 + videos. Managed and analyzed performance data for a content covering travel, book reviews and product reviews.
Monitored KPIs including Views, Watch Time, Subscribers, CTR and Audience Retention using YouTube Studio Analytics.
Analyzed audience segmentation (new vs returning viewers, active hours, demographics) to refine content strategy.
Built foundational skills in KPI tracking, trend analysis, and behavioral data interpretation.

Computer Instructor — KV Command Hospital 2018 – 2019

Created analytical reports using SQL and Excel to track student performance and administrative metrics.
Improved data accuracy and reporting efficiency through structured data management.

Technical Analyst — Cognizant 2010 – 2014

Conducted SQL-based data validation and process optimization.
Collaborated with cross-functional teams in Agile environment for requirement gathering and delivery.
Improved CRM workflows resulting in 10% enhancement in process efficiency.

Senior Software Engineer — iGate/Capgemini 2007 – 2009

Performed data validation, cleansing, and quality checks for retail domain datasets.
Supported DQM initiatives that improved data reliability and compliance.

Awards & Certificate.

Deloitte Australia - Data Analytics Job Simulation

Comcast - Unspoken Interview Fundamentals Job Simulation

Excel: Mother of Business Intelligence

Get Job Ready: Power BI Data Analytics for All Levels 3.0

SQL Beginner to Advanced For Data Professionals

Codebasics Resume Project Challenge

Microsoft Certified: Power BI Data Analyst Associate

Contact.

Feel free to get in touch with me. I am always open to discussing new projects, creative ideas or opportunities to be part of your visions.

Download CV

[email protected]

Call Me

+91 7044689553

https://www.linkedin.com/in/mahato-rita/

GitHub

https://github.com/Rita-Mahato-2025

PowerBI Project

QuickBites Crisis Analysis & Recovery Strategy

Domain/Function: Food Delivery & Consumer Analytics

This project analyzes Sales & Customer data during operational crisis. Identified key loss drivers, and recommended targeted recovery strategies, optimizing revenue and improving customer retention.

View Project
Engagement

View Project
on GitHUB

Other Tools

SQL

Python

Power BI

QuickBites Crisis Analysis & Recovery Strategy

Overall decline in Orders is 69%. Dropped from approx 113K to 35K.

Negative keywords dominated feedback: stale, cold, terrible, horrible, late, unhygienic, disappointing

Project Details

QuickBite faced a sudden sales drop after a viral social media video raised hygiene concerns, followed by a weeklong delivery outage due to monsoon disruptions.

I analyzed sales, operations, and customer feedback using SQL and Python to quantify the impact and identify recovery priorities. Power BI dashboards highlighted revenue losses by outlet and region.

Recommendations :
Immediate (0–72 hrs) — Contain damage
• Stop & isolate: pause orders from top 5 SKUs / vendors / warehouses that show highest negative-review density (filter by keywords + returns). Owner : Ops/ Merchandising
• Customer triage & goodwill: proactively identify customers from June with negative reviews / cancellations and send apologies + offer refunds/discount vouchers (prevent churn). Owner: CX & CRM (72h).
• Public messaging: short, transparent comms across app/email acknowledging issues and stating corrective steps — reduces escalation. Owner: Marketing + Legal.

Live Interactive Dashboard

PowerBI Project

Shield Insurance Analysis

Domain/Function: Insurance

This project focuses on analyzing customer demographics, revenue performance, policy behavior, and settlement patterns for Shield Insurance. The objective was to enable business teams to identify high-value customer groups, evaluate sales channels, and support strategic decision-making.

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Engagement

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on GitHUB

Revenue trend month-wise shows steady growth with a seasonal spike around March.

The 31–40 age group dominates with the highest number of customers and revenue, making it our core segment.

Project Details

The client lacked clarity on:
• Revenue trends across channels and age groups
• City-wise performance and customer distribution
• Settlement percentage patterns
• Monthly policy and premium fluctuations
The goal was to build an end-to-end analytics solution to improve visibility and guide business prioritization.

Insights
• Sales mode preference is similar across age group.
• Policy preferences are similar across all age-group.
• Aligning product, channel, and engagement strategies by age group can significantly improve acquisition efficiency and customer lifetime value.

Recommendations
Align sales modes with age-specific preferences to improve acquisition efficiency.
Customize policy offerings based on dominant preferences within each age segment.

With these strategies, we can improve acquisition in low-performing segments and enhance profitability of high-contributing age groups.

Live Interactive Dashboard

PowerBI Project

Customer Churn Analysis

Domain/Function: Subscription-Based Business / SaaS (Software as a Service) Analytics

Analyzed customer churn (Sept 2025–Feb 2026) for a SaaS company: overall churn 15.75%, highest in Basic plan (22%), Europe shows $680 revenue risk. Recommendation: target Basic users in Europe with upsell & retention strategies.

View Project
on GitHUB

The dashboard shows SaaS churn analysis: 400 total customers, 63 churned (15.75%). Basic plan has highest churn (21.93%). Revenue loss is highest in Europe ($680), followed by India, APAC, and North America, highlighting retention and revenue risks.

For the Basic plan, out of 187 customers, 41 churned (21.93%). Revenue lost by region is highest in Europe ($240), followed by India ($220) and North America ($200).

Project Details

Churn & Revenue Risk Analysis for SaaS Company
As a Data Analyst, I analyzed customer-level subscription data from Sept 2025 to Feb 2026 to evaluate churn behavior and its impact on revenue. The overall churn rate was 15.75%, with the Basic plan showing the highest attrition at 22%, while Pro and Enterprise plans maintained lower churn (~10–11%). Revenue risk was concentrated in Europe, with churn-driven losses totaling $680. Analysis revealed that higher-value plans improve customer stickiness, and lower-tier customers are more price-sensitive. Based on these insights, I recommended targeted retention strategies, including upselling Basic users to higher-tier plans and accelerating onboarding to reduce churn, particularly in high-risk regions. Tools used included Excel (pivot tables & calculated fields), SQL (CASE WHEN + GROUP BY), and Python (groupby + conditional logic). This project highlights the importance of combining behavioral and revenue insights to guide actionable business

Live Interactive Dashboard

PowerBI Project

Sales & Inventory Analysis Case Study

Domain/Function: Retail / E-commerce Analytics

This project analyzes sales, profit, and inventory performance across products and stores to derive actionable business insights. The goal is to identify top-performing products, evaluate store efficiency, and understand the impact of stock availability on sales.

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Engagement

View Project
on GitHUB

The Power BI dashboard includes: • Bar charts for revenue and profit comparison • Column chart for store profit margins • KPI cards for stock availability

• Clustered bar chart for stock availability vs sales impact • Conditional formatting to highlight top performers

Project Details

Business Questions Answered :
1. Which product generated the highest total revenue?
2. Which product has the highest total profit?
3. Which store has the lowest overall profit margin?
4. How often did stock unavailability occur?
5. Does stock availability impact sales volume?

Live Interactive Dashboard

SQL Project

AtliQ Hardwares Sales & Finance Analytics Project

Domain/Function: Retail & Consumer Electronics

This project uses SQL to analyze and automate AtliQ Hardware’s growing sales data. By creating fast, reliable reports and applying key business rules, it improved data accuracy and uncovered actionable insights that support data-driven decision-making.

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Engagement

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on GitHUB

AtliQ Hardwares Sales & Finance Analytics Project

SQL report summarizing Croma India’s monthly sales by product, variant, sold quantity, and gross revenue.

SQL report showing Croma India’s total gross sales per month to track revenue trends and performance.

Project Details

Explored AtliQ Hardware’s growing sales database to improve
reporting and analysis efficiency.
Automated recurring and ad-hoc business reports, applying
business rules to ensure data accuracy.
Delivered faster insights and supported data-driven
decision-making through efficient SQL solutions.

PowerBI Project

Business Insights 360 Dashboard for Finance, Sales, Marketing and Supply Chain

Domain/Function: FMCG

My goal is to implement an advanced Power BI analytics solution at AtliQ Hardwares, transforming Excel-based reports into interactive dashboards to drive insights and enable data-driven decision-making for better competitiveness.

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Engagement

View Project
on GitHUB

Business Insights 360 Dashboard for Finance, Sales, Marketing and Supply Chain

Data modeling involving 15+ tables

User-empathetic landing page as a part of dashboard design

Project Details

Project Goal:

Create a single Power BI report usable by stakeholders across Sales, Marketing, Finance, and the Executive team.

Focus on:

Robust Data Modeling

User-empathetic Report Design

Drillable Insights

What I Learned:

Power Query (Basic & Advanced Operations)

Basic & Complex DAX formulas

Data Modeling across 10+ tables

Choosing the right visuals & formatting

Dashboard Design Principles

Using Bookmarks

Deploying in Power BI Service

Implementing Stakeholder Feedback

Metrics across Sales, Marketing, Finance & Supply Chain

Live Interactive Dashboard

Excel Project

Sales Analytics(FMCG)

Domain/Function: FMCG

Developed two detailed reports for the sales team, enabling them to evaluate customer performance more effectively and assess overall market performance in comparison to their set targets, supporting data-driven decision-making.

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Engagement

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on GitHUB

Customer Performance Report: Shows each customer's net sales trends and year-over-year performance at a glance.

Market vs Target Report: Tracks yearly market performance against targets, helping stakeholders evaluate progress and gaps.

Project Details

Project Summary:
In this project, I designed a comprehensive sales report in Excel using Pivot Tables to help businesses make data-driven decisions. The report supports determining optimal customer discounts, strengthening consumer negotiations, and identifying potential expansion opportunities in high-growth markets.

The insights generated from the report provide actionable recommendations that enable businesses to refine sales strategies, improve customer satisfaction, and maximize revenue.

Key Learnings & Skills Acquired:

Pivot Tables

Power Query

Basic DAX

Conditional Formatting

Report Design & Visualization

Sales Domain Metrics

Outcome:
This project highlights how sales data analysis can empower organizations to track performance, evaluate market opportunities, and enhance sales efficiency. By leveraging these insights, businesses can uncover growth opportunities, stay competitive, and drive sustainable success.

Python Project

Diwali Sales Analysis

Domain/Function: Retail & E commerce

This Python capstone project showcases the application of data manipulation, visualization, automation, and problem-solving. It delivers a real-world solution through an end-to-end data analysis workflow, highlighting practical skills and analytical thinking.

View Project
on GitHUB

From above graphs, we can see that most of the buyers are working in IT Sector, Healthcare and Aviation.

From the above two graphs, we can see that most of the orders and total sales/ amount are from Uttar Pradesh, Maharashtra and Karnataka respectively

Project Details

Diwali Sales Analysis – Python Capstone Project

This Python capstone project marks the culmination of skills gained throughout the course by integrating data manipulation, visualization, automation, and problem-solving into a complete analysis workflow. The focus is on analyzing Diwali sales data to uncover customer buying behavior, festive spending patterns, and top-performing product categories, highlighting both analytical thinking and business relevance.

Objective:

Apply Python programming to solve a real-world business problem.

Generate actionable insights from retail sales data.

Strengthen knowledge of key libraries (Pandas, NumPy, Matplotlib, Seaborn).

Improve coding practices and showcase the ability to design, implement, and present an end-to-end solution.