📊 Data Analysis Portfolio

Hi, I’m Anusha 👋 This repository contains my hands-on data analysis work, showcasing my ability to analyze real-world datasets, derive insights, and present findings using Python, Power BI, and Tableau.

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📁 Repository Structure

Data-Analysis/
│
└── Projects/
    ├── Customer-Transaction-Analytics/
    ├── Linkedin-Analytics/
    └── Sales-Performance-Analytics/

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🚀 Projects

The Projects/ folder contains end-to-end, portfolio-ready projects designed to reflect real-world analytics tasks.

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1️⃣ Sales Performance & Revenue Analytics

📂 Folder: Projects/Sales-Performance-Analytics/

Objective: Analyze sales data to uncover revenue trends, product performance, pricing behavior, and seasonality.

Key Highlights:

• 113k+ transaction-level records
• Revenue, profit, and AOV analysis
• Monthly trend & seasonality detection
• Product category performance (Pareto principle)
• Outlier detection using IQR
• Correlation & pricing analysis
• Exploratory A/B testing (non-causal)

Tools Used: Python (Pandas, Matplotlib, Seaborn, SciPy), Tableau

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2️⃣ Customer Transaction Analytics (Power BI Project)

📂 Folder: Projects/Customer-Transaction-Analytics/

Objective: Build an interactive business dashboard to analyze customer transactions and key performance metrics.

Key Highlights:

• Transaction-level analysis
• KPI creation (Revenue, Profit, Orders, AOV)
• Customer behavior and spending patterns
• Interactive filtering and drill-down analysis
• Business-ready dashboard design

Tools Used: Power BI, Python (for preprocessing & validation)

Outcome: Delivered an interactive Power BI dashboard enabling stakeholders to quickly understand customer performance and revenue drivers.

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3️⃣ LinkedIn Analytics (Job Search & Networking Analysis)

📂 Folder: Projects/Linkedin-Analytics/

Objective: Analyze personal LinkedIn data to evaluate job search effectiveness and networking behavior.

Key Highlights:

• Job search funnel (Saved → Applied conversion)
• Application trends over time
• Role targeting analysis
• Network leverage (Followed vs Applied companies)
• Messaging activity analysis
• Skills frequency analysis

Tools Used: Python (Pandas, Matplotlib)

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🛠️ Tools & Technologies

• Languages: Python

• Visualization & BI: Power BI, Tableau

• Libraries: Pandas, NumPy, Matplotlib, Seaborn, SciPy

• Concepts:

  • Exploratory Data Analysis (EDA)
  • Descriptive & inferential statistics
  • Business analytics & storytelling

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🎯 What This Portfolio Demonstrates

✔ End-to-end analytics projects

✔ Business-focused dashboards

✔ Strong visualization skills (Power BI & Tableau)

✔ Statistical thinking & data cleaning

✔ Clear communication of insights

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📬 Contact

Anusha

Aspiring Data Analyst