📊 Amazon Data Analyst Prep

A structured 30-day prep system for Amazon Data Analyst interviews — covering SQL from basics to advanced, Python data analysis, Tableau dashboards, and real-world case studies modeled on Amazon's actual interview rounds.

📌 What's Inside

Topic	What's Covered
🗄️ SQL (Days 1–7)	SELECT, filtering, aggregation, JOINs, subqueries, CTEs, window functions, performance tuning
🐍 Python (Days 8–11)	Data cleaning, transformation, EDA, statistical analysis, A/B testing, cohort analysis, CLV
📊 Tableau (Days 21–25)	Sales dashboards, customer analytics, operational KPIs
🔎 Case Studies (Days 12–20)	Sales analysis, customer retention, warehouse operations
🎯 Behavioral (Days 26–30)	Amazon Leadership Principles answered using the STAR method

🗓️ 30-Day Progress Tracker

Days	Topic	Status	Deliverable
Day 1	Basic SELECT Queries	✅ Complete	15 exercises
Day 2	Filtering & Aggregation	✅ Complete	15 exercises
Day 3	SQL Joins	✅ Complete	10 exercises
Days 4–5	Subqueries, CTEs, Window Functions	✅ Complete	20 exercises
Days 6–7	Advanced Queries & Performance Tuning	✅ Complete	20 exercises
Days 8–9	Python Data Cleaning & Transformation	✅ Complete	11 functions
Days 10–11	EDA & Statistical Analysis	✅ Complete	A/B testing, CLV, Cohort
Days 12–14	Case Study 1: Sales Analysis	✅ Complete	Full solution
Days 15–17	Case Study 2: Customer Retention	✅ Complete	Full solution
Days 18–20	Case Study 3: Operational Analytics	✅ Complete	Full solution
Days 21–25	Tableau Dashboard Design	✅ Complete	3 dashboards
Days 26–30	Interview Prep & Mock Questions	✅ Complete	30+ Q&A

🛠 Tech Stack

PostgreSQL · Python 3.10+ · Pandas · NumPy · Matplotlib · Seaborn · SciPy · Tableau Public

📁 Repository Structure

Amazon-data-analyst-prep/
├── SQL/
│   ├── Day1_Basic_SELECT.sql              # SELECT, WHERE, ORDER BY, LIMIT, DISTINCT
│   ├── Day2_Filtering_and_Aggregation.sql # GROUP BY, HAVING, COUNT/SUM/AVG/MIN/MAX
├── Day-3-joinss/
│   └── day3_joins.sql                     # INNER/LEFT/RIGHT/FULL OUTER/CROSS/Self/Anti-join
├── Sql Practice/
│   └── Filttering_and_Aggregation.sql     # Additional aggregation practice
├── Case-Studies/                          # 3 full case study solutions
├── amazon_sql_days_4_7.sql                # Subqueries, CTEs, Window Functions, Perf Tuning
├── amazon_python_days_8_11.py             # Data Cleaning → EDA → Stats → CLV → A/B Test
├── amazon_interview_prep.md               # 30+ SQL/Python Q&A + STAR behavioral answers
├── amazon_repo_README.md                  # Full 30-day curriculum breakdown
└── requirements.txt

📖 Key Files

File	Description
amazon_sql_days_4_7.sql	Advanced SQL — CTEs, window functions, query optimization
amazon_python_days_8_11.py	Python module — cleaning → EDA → stats → CLV → A/B test
amazon_interview_prep.md	Interview Q&A with full solutions + STAR answers
amazon_repo_README.md	Full 30-day curriculum with day-by-day breakdown

🚀 Quick Start

git clone https://github.com/kamjula/Amazon-data-analyst-prep.git
cd Amazon-data-analyst-prep
pip install -r requirements.txt
python amazon_python_days_8_11.py

👩‍💻 Author

Sravani Kamjula | Data Analyst   LinkedIn · Portfolio