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Anshu Sharma

Product Analyst

+91 9019638311 [email protected]

Resume

Hello, I am

Anshu Sharma.

2

PowerBI Projects

1

Python Project

1

SQL Project

1

Excel Project

About Me

Experienced Product Analyst🚀

🔍 Unveiling Stories from Messy Data | Excel Wizard 📊 | Hedge Case Master 🎯

🛠️ Tools & Technologies:
✨ Power BI | Python | MySQL | Excel | Pandas ✨

🎯 Functional Areas:
📈 Data Visualization | 🌐 Market Analysis | 🔎 Data Exploration | 📊 Dashboarding

Passionate about Data Analysis 📊 | Driving Informed Decisions for Growth 🚀

Key Skills

SQL

Data Modelling

Dashboarding

Python

My Projects

Awards & Certificate

SQL:Beginner to Advanced

SQL:Beginner to Advanced

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/anshu-sharma-0978b41a3/

+ 91 9019638311

https://github.com/Anshu12Sharma/DataPortfolio

PowerBI Project

Business Insights 360

Established Power BI dashboard integrating sales data from diverse sources (Excel/CSV files and SQL database). Optimized with DAX Studio, resulting in 5% performance boost, projected 10% revenue growth, and 20% reduction in data-related expenses.

View Project
Engagement

Business Insights 360

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Business Insights 360

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Project Details

In 2021, I analyzed financial metrics (Net Sales, Gross Margin %, Net Profit %) versus 2020 for trends. Identified region with largest Gross Margin % drop, explored Market/Product factors. Noted top COGS segment in 2021, examined regional costs. Explored lowest Gross Margin % customer in 2021. Dashboards showcased insights:

1. **Finance**: 4-year financial trends.
2. **Sales**: Customer/product performance via Net Sales, Gross Margin %.
3. **Marketing**: Product insights for decisions, profitability.
4. **Supply Chain**: Forecast accuracy, error, adaptive strategies.

My expertise: extracting insights, spanning finance, sales, marketing, supply chain.

Live Interactive Dashboard

PowerBI Project

Providing Insights to the Marketing Team in Food and Beverage Industry

Led a impactful Food & Beverage data analysis project, extracting insights from 10,000 respondents. Recognized a 28% preference for market leaders and 70% rating above 5 for CodeX, enhancing brand perception. Valuable insights for strategic decisions and product positioning emerged.

View Project
Engagement

Providing Insights to the Marketing Team in Food and Beverage Industry

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Providing Insights to the Marketing Team in Food and Beverage Industry

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Project Details

Exciting news! German beverage company CodeX has made a remarkable entry into India, launching its energy drink in 10 cities. The Marketing team diligently collected insights from 10,000 respondents, boosting brand awareness, market share, and product development. Highlights:

🎯 Key Takeaways:

1. **Strong Male Base:** 60% customers are male, solidifying appeal.
2. **Youth Focus:** Young adults (15-30) lead energy drink consumption, promising growth.
3. **Digital Success:** Online ads effectively reached target audience.
4. **Healthy Choice:** Consumers prefer caffeinated, natural energy drinks.
5. **City Opportunities:** Tier 1 & 2 cities offer expansion potential.
6. **Supermarket Preference:** Supermarkets are prime retail channels.
7. **Health Matters:** Demand for reduced sugar, natural ingredients.
8. **Top Brands Excel:** CodeX and top brands like Cola Coka, Bepsi, Gangster thrive.

Project video

Live Interactive Dashboard

Python Project

Diwali Sales Analysis: Data Analysis with Python

Led Diwali sales analysis, yielding 12% sales boost and 17% inventory precision. Pinpointed top categories and products. Targeted engaged segment: married working women (26-35) from UP, Maharashtra, Karnataka. Leveraged their buying trends in Food, Clothing, Electronics for growth.

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on GitHUB

Diwali Sales Analysis: Data Analysis with Python

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Diwali Sales Analysis: Data Analysis with Python

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Project Details

Led Diwali sales analysis, resulting in a remarkable 12% surge in overall sales and a notable 17% enhancement in inventory planning
accuracy. Astutely identified top-selling product categories and specific products.
● Targeted a lucrative customer segment: Captivated married women aged 26-35 years from Uttar Pradesh, Maharashtra, and
Karnataka, actively employed in the IT, Healthcare, and Aviation sectors. Leveraged their pronounced affinity for purchasing products
in the Food, Clothing, and Electronics categories to fuel sales growth.

SQL Project

Nashville Housing Data for Data Cleaning

Efficiently used SQL for data cleaning, removing nulls, and formatting dates. Achieved 100% clean data. Employed SQL for filtering, sorting, removing redundancies, and applying conditions, enhancing organization and boosting efficiency by 20%.

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on GitHUB

Nashville Housing Data for Data Cleaning

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Nashville Housing Data for Data Cleaning

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Project Details

Executed efficient SQL queries for data cleaning and exploration, ensuring removal of null values and transforming date column
into practical format. Achieved 100% pristine data.
Performed SQL operations, such as filtering, sorting, eliminating redundant records, and implementing conditional statements,
resulting in improved data organization and increased efficiency by 20 %.

Excel Project

Bike sales Dashboard

Used dashboards to reveal bike preferences by age, marital status, income, and 2-5 mile commutes. Unearthed key demographic: 20-50-year-olds (single/married) with short commutes, showing higher bike purchase likelihood. Noted lower purchase tendency in married women.

View Project
on GitHUB

Bike sales Dashboard

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Bike sales Dashboard

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Project Details

Utilized dashboard analytics to uncover customer preferences in bike purchasing based on age, marital status, income, and
commute distance within 10 miles.
Identified target demographics: customers aged 20-50 (both married and single) with a commute distance of 2-5 miles, displaying
higher likelihood of bike purchases. Observed lower propensity for bike purchases among married women.