Powered by
Codebasics DA Bootcamp

Vivek Yadav

Data Engineer

+91 9760022725 [email protected]

Resume

Hello, I am

Vivek Yadav.

2

Excel Projects

2

PowerBI Projects

2

SQL Projects

About Me

Hello! 👋 I'm Vivek Yadav, a skilled Data Engineer with a strong foundation in designing, building, and optimizing data pipelines. I specialize in transforming raw data into structured, high-performance datasets that drive business insights. My expertise includes SQL, ETL processes, data modeling, and automation, ensuring seamless data integration from multiple sources.

I am proficient in optimizing data workflows, developing scalable data warehouses, and implementing best practices for data governance and quality. With hands-on experience in Python, Power BI, and cloud technologies, I build robust data solutions that empower teams with reliable, actionable insights.

Passionate about solving real-world problems through data, I aim to enhance decision-making and create efficient, data-driven ecosystems for organizations. 🚀

Key Skills

SQL & Database Management

ETL (Extract, Transform, Load) Pipelines

Data Warehousing

Big Data Technologies

Cloud Platforms

Python for Data Engineering

Data Pipeline Orchestration

Data Modeling

API & Data Integration

My Projects

My Experience

Galactic Client Services ( Data Engineer ) [ July 2024 - Jan 2025]

AtliQ technologies ( Data Engineer ) [ April 2024 - June 2024 ]

Let's Connect

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.

[email protected]

https://www.linkedin.com/in/vivek-yadav-13a016267/

+ 91 9760022725

https://github.com/vivekyadavformal

Excel Project

Profit & Loss statement

Generated a comprehensive P&L report for AtliQ Hardware FY 2022, utilizing advanced features in Excel such as Pivot Tables and DAX to provide granular insights into revenue streams and expense categories

Profit & Loss statement

Atliq's Market performance

Profit & Loss statement

Atliq's P & L Matrics comparison

Project Details

Generated a comprehensive P&L report for AtliQ Hardware FY 2022, utilizing advanced features in Excel such as Pivot Tables and DAX to provide granular insights into revenue streams and expense categories.
● Automated the data cleaning using Power Query, which can rescue around 4 hrs of repeated manual work.
● As it used DAX measure for calculations, it provided a better user experience and flexibility.

PowerBI Project

Business Insights 360

Brick & Mortar and E-commerce Customized a multi-functional Power BI dashboard to analyze AtliQ hardware's sales trends over the global market by gathering data from 2 different sources (Excel/CSV files and an SQL database).

Business Insights 360

Home page

Business Insights 360

Executive View

Project Details

This project, which combines Power BI, SQL, and Excel, centers around addressing operational issues at AtliQ Hardware, a prominent global consumer electronics company. The company's heavy reliance on Excel for data analysis has led to significant losses in some regions. To rectify this, senior management aims to initiate a data analytics project, leveraging data from the previous year to enhance performance and drive improvements.
💼Finance View: shows profit and loss statements like GM, NP, NS etc, and performance over time chart w.r.t to key matrices.
📣Sales View: Shows customers and product performance, unit economics, and performance matrix by NS and GM%
📣 Marketing View: Shows region and product performance, unit economics, and performance matrix by NS and GM%
🚚 Supply Chain View: shows forecast accuracy, Net Error, trends, and key matrices by customers and products.
👨‍🎓 Executive View: shows market share of competitors, trends, revenue by division and channel, top 5 customer

Live Interactive Dashboard

Excel Project

Accenture North America Data Analytics and Visualization Job Simulation

Crafted two reports for the client: one unveils the top 5 popular content categories, while the other details which category received the most reactions each month.

Accenture North America Data Analytics and Visualization Job Simulation

Structured approach boosts understanding, data quality, models, analysis, and decision-making.

Accenture North America Data Analytics and Visualization Job Simulation

Top 5 most popular categories of content

Project Details

Social Buzz, founded by ex-engineers from a social media giant, prioritizes content with user anonymity. With 500 million monthly active users, they need scaling oversight. Their vast data creation requires sophisticated tech. Seeking guidance for an IPO, scaling challenges, and data best practices, they aim to leverage external expertise for sustained growth.
In my capacity as a data analyst for Accenture, I cleaned, modeled, and examined seven datasets to bring forth content trends for strategic choices. For the client and internal teams, I also created a PowerPoint and video presentation that included important findings.

Project video

PowerBI Project

PhoneNow Customer Satisfaction and Performance Dashboard

Domain/Function: Business Intelligence

PhoneNow, the call center needed KPI's regarding: a) Overall customer satisfaction. b) Calls answered/abandoned analysis. c) Calls by time. d) Average speed of answer. e) Agent performance quadrant: handle time vs calls answered.

PhoneNow Customer Satisfaction and Performance Dashboard

Call center

PhoneNow Customer Satisfaction and Performance Dashboard

Image

Project Details

To fulfill PhoneNow's needs, the dataset was first imported and modeled in Power BI. Then, A dashboard was designed showcasing:

Overall customer satisfaction with gauges.
Calls analysis (answered/abandoned) using line/bar charts.
Calls by time with heatmaps or line charts.
Average speed of answer as a KPI.
Agent performance quadrant with average handle time vs calls answered.
Interactive filters for date, agent, or department.
Visual enhancements for clarity.
Logical layout for easy interpretation.

Live Interactive Dashboard

SQL Project

Investment Portfolio

Domain/Function: Finance

Developed an SQL-based "Investment Portfolio" project to analyze financial data. Queries provide insights into portfolio performance, asset holdings, profit/loss, and transaction trends. Have optimized database queries for actionable insights into investment decisions.

View Project
on GitHUB

Investment Portfolio

Find the total value of assets in each portfolio

Investment Portfolio

Finding the Asset Holdings of an Investor

Project Details

This project involves creating a relational database system to manage investment portfolios using MySQL.
It includes tables for Investors, Portfolios, Assets, Transactions, and MarketPrices.
The system tracks asset transactions (buy/sell), portfolio performance, and historical market prices.

Key features include:
Database Design: Created a normalized schema for efficient storage of investor, portfolio, and asset data.
Transaction Management: Handled asset transactions, including buy/sell operations with quantities and prices.
Market Price Tracking: Stored and analyzed historical market prices for assets like equities, bonds, and commodities.
SQL Queries: Used advanced SQL queries to analyze portfolio performance and asset transactions, including joins, aggregates, and subqueries.

This project showcases proficiency in SQL, database design, and querying to simulate real-world investment portfolio management.

SQL Project

Retail Store Data Insights: Analyzing Sales, Inventory, and Performance with SQL

Domain/Function: Data Analysis and Business Intelligence

Analyzed retail store data using SQL to uncover insights into sales performance, inventory management, and product trends. Key findings included top-performing stores, product category sales, out-of-stock analysis, and inventory optimization opportunities for better decision-making.

View Project
on GitHUB

Retail Store Data Insights: Analyzing Sales, Inventory, and Performance with SQL

Top 3 stores with the Highest sales

Retail Store Data Insights: Analyzing Sales, Inventory, and Performance with SQL

Total sales for each store where total sales exceed 10,00,000 INR

Project Details

This project focuses on analyzing retail store data using SQL to drive operational efficiency and strategic decision-making. Queries were developed to identify the top 3 stores with the highest sales in the last year, calculate total sales per store grouped by product categories (highlighting stores exceeding 1,000,000 INR in sales), and detect products out of stock in more than 50% of stores. Additionally, an analysis of store-product combinations with more than 100 units in stock provided insights into potential overstock issues. The project highlights the use of SQL techniques such as joins, grouping, and subqueries to derive actionable insights. These findings empower businesses to optimize sales strategies, improve inventory management, and enhance overall profitability in the competitive retail sector.