Transforming complex datasets into actionable business insights through data visualization, analytics, and business intelligence.
Data Analyst with 17 months of experience at Tata Consultancy Services (TCS), including 1 year as an SAP Analytics Cloud Developer building enterprise dashboards and KPI reports for a Germany-based global MNC client.
Skilled in Python, SQL, Power BI, Tableau, and Advanced Excel with hands-on experience in data cleaning, EDA, data modelling, dashboard development, and KPI reporting. Adept at transforming complex datasets into actionable business insights to support data-driven decision-making.
📍 Visakhapatnam - 530008, Andhra Pradesh, India 📞 +91 9573742803 📧 swaroop.vathada@gmail.com 🔗 LinkedIn | 💻 GitHub
swaroop456.github.io/
├── index.html ← Main Portfolio Website
└── assets/
└── Amazon_dataset_Dashboard.pdf ← Power BI Amazon dataset Dashboard
├── Financial_Sales_Dashboard.pdf ← Power BI Financial Dashboard
├── HR_Analytics_Dashboard.pdf ← Power BI HR Dashboard
├── resume.pdf ← Data Analyst Resume
└── Tableau_Mini_Project_Dashboard.pdf ← Tableau Store Sales Dashboard
Date: May 2026 | Repo: Amazon-Orders-Data-Analytics-Projec • Performed end-to-end analysis on Amazon Orders Dataset containing 1,13,698+ records and 29 columns spanning Jan 2022 – Sep 2022 using Python, Excel, MySQL Workbench, and Power BI. • Executed data cleaning, preprocessing, and exploratory data analysis (EDA) using Python libraries — Pandas, NumPy, Matplotlib, and Seaborn — improving dataset quality and uncovering key sales and customer behaviour trends. • Built 5-page interactive Power BI Dashboard and Excel KPI reports analysing revenue, product categories, fulfilment performance, promotions, and geographic sales distribution across India. • Identified that Kurta and Set categories contribute 77% of total orders, while Maharashtra and Karnataka are the top revenue-generating states with Bengaluru, Hyderabad, and Mumbai as premium revenue cities. • Derived actionable business insights revealing promoted orders generate 2.5x higher revenue, expedited shipping contributes nearly 75% of total revenue, and September & May are the peak sales months for Amazon fashion sales.
Tech stack: Python Pandas Numpy Matplotlib EDA SQL MYSQL Excel Power BI
Date: Apr 2026 | Repo: Power_BI_Financial_Sales_Dashboard
- Imported Microsoft Financial Sample dataset (700 rows, 16 columns) into Power BI Desktop
- Built 6 DAX measures — Total Sales (118.73M), Total Profit (16.89M), Total Units Sold (1.13M), Total COGS (101.83M), Total Discounts (9.21M), Profit Margin % (14.2%)
- Designed a 4-page interactive dashboard — Financial Overview, Product Analysis, Country Analysis, Yearly Trends (15 visuals)
- Government segment drives 44.22% of total sales (52.5M) and 65.04% of total profit
- Time intelligence: October 2014 was peak sales month at 12.4M
Tech Stack: Power BI Desktop Power BI Service DAX Power Query Time Intelligence KPI
Date: Apr 2026 | Repo: Power_BI_HR_Analytics_repo
- Developed 7 DAX measures — Total Employees (1,480), Attrition Rate % (16.08%), Active Employees (1,242), Avg Monthly Income (6,500), Avg Age (36.9), Avg Job Satisfaction (2.73/4)
- Built 4-page interactive dashboard — Attrition Overview, Attrition Analysis, Employee Insights, HR Summary (16 visuals)
- Uncovered 6 critical attrition drivers: R&D dept leads with 133 employees lost; employees earning below ₹5,000/month account for highest attrition (163 employees)
- Published to Power BI Service for live cloud-based access
Tech Stack: Power BI Desktop Power BI Service DAX Power Query ETL HR Analytics
Date: Apr 2026 | Repo: Tableau_Store_sales_dashboard_repo
- Connected and explored raw retail sales dataset of 31,047 records (21 columns, full year Jan–Dec 2022)
- Built 7 interactive chart types — Line Chart, Horizontal Bar Chart, Pie Chart, Top 10 States Bar Charts
- Created a 5-point Tableau Story — Sales Peaked in March 2022, Amazon is Top Selling Channel
- Derived 8 key business insights: Amazon leads all 7 sales channels; Maharashtra is #1 state; 92% of 31,047 orders successfully delivered
Tech Stack: Tableau Desktop Data Storytelling Visualization Dashboard Cross-filter
Date: Mar 2026 | Repo: Advanced_Excel_Retail_Sales_Analysis_repo
- Performed end-to-end data cleaning on 12,575 rows (2022–2025) — resolved 6,625 blank cell issues across 5 columns
- Applied 17 Advanced Excel formulas — SUMIFS, XLOOKUP, UNIQUE, SORT, FILTER, LARGE, Nested IF with Dynamic Arrays
- Total revenue: $1,552,071 | Avg order value: $129.65 | Butchers: highest category ($208,118) | Cash: top payment ($537,710)
- Performed What-If Analysis using Goal Seek & Scenario Manager — modelled 3 scenarios (Low: $50, Base: $200, High: $500)
Tech Stack: Advanced Excel Pivot Tables XLOOKUP Goal Seek Scenario Manager
Date: Mar 2026 | Repo: MYSQL_Classic_models_DB_Analysis_repo
- Analysed the Classic Models relational sales database using 10 structured SQL queries
- Applied advanced SQL — JOIN, GROUP BY, SUM, AVG, COUNT, and date functions across 10 analytical problem statements
- Delivered executive-level SQL analysis report covering revenue concentration, customer dependency, seasonal trends, and inventory gaps
Tech Stack: MySQL SQL JOIN Aggregate Functions Data Analysis
Date: Feb 2026 | Repo: Python_Pandas_Project_repo
- Performed end-to-end data cleaning and preprocessing on 10,000+ rows of raw cafeteria transactional sales data using Python and Pandas
- Conducted EDA and identified that purchases between 2–7 units are the highest revenue contributors
- Derived 3 actionable business recommendations — tiered pricing strategy, limiting bulk discounts, and value-based pricing
Tech Stack: Python Pandas NumPy Matplotlib EDA
| Category | Skills |
|---|---|
| Programming Languages | Python, SQL |
| Python Libraries | Pandas, NumPy, Matplotlib |
| Database & Tools | MySQL, MySQL Workbench |
| Analytics & BI Tools | SAP Analytics Cloud, Power BI Desktop, Power BI Service, Tableau Desktop, Advanced Excel |
| Data Analytics | Power Query, DAX, Data Visualization, EDA, Data Cleaning, Business Intelligence, KPI, Dashboards, Data Modelling, ETL |
| Core Concepts | Data Structures, CRUD Operations, Data Cleaning, Basic OOP Concepts |
| Version Control | Git, GitHub |
Tata Consultancy Services (TCS) — Hyderabad, India 📅 May 2024 – October 2025
📅 Aug 2024 – Aug 2025
- Worked as an SAP Analytics Cloud Developer on the Ledvance Digital Future (LDF) enterprise analytics project
- Developed 5+ interactive dashboards and KPI tracking reports using SAP Analytics Cloud
- Analysed 5–7 datasets in SAP Analytics Cloud for data transformation and reporting
- Built and optimized 5–7 data models ensuring 30% improvement in data reliability
- Ensured data accuracy, consistency, and integrity across all reporting layers — 40% improvement in business outcomes
- Delivered analytics solutions aligned with cross-functional teams
B.Tech — Mechanical Engineering Avanthi Institute of Engineering and Technology 📅 July 2019 – April 2023 | CGPA: 7.18
| Certification | Issuer | Date | Level |
|---|---|---|---|
| Exploring SAP Analytics Cloud — Record of Achievement | SAP | Oct 2024 | Foundational |
| Platform | Link |
|---|---|
| 🌐 Portfolio | Data_Analyst_Portfolio |
Transforming complex datasets into actionable business insights through data visualization, analytics, and business intelligence.
Data Analyst with 17 months of experience at Tata Consultancy Services (TCS), including 1 year as an SAP Analytics Cloud Developer building enterprise dashboards and KPI reports for a Germany-based global MNC client.
Skilled in Python, SQL, Power BI, Tableau, and Advanced Excel with hands-on experience in data cleaning, EDA, data modelling, dashboard development, and KPI reporting. Adept at transforming complex datasets into actionable business insights to support data-driven decision-making.
📍 Visakhapatnam - 530008, Andhra Pradesh, India 📞 +91 9573742803 📧 swaroop.vathada@gmail.com 🔗 LinkedIn | 💻 GitHub