Reorder Patterns for Amazon Fresh

Company:Amazon
Dawn AI

Welcome to Interview Master! 👋

I'm here to help you practice Reorder Patterns for Amazon Fresh - a Data interview question from Amazon.

Problem Overview

As a Data Analyst on the Amazon Fresh product team, you and your team are focused on enhancing the customer experience by streamlining the process for customers to reorder their favorite grocery items. Your goal is to identify the most frequently reordered product categories, understand customer preferences for these products, and calculate the average reorder frequency across categories. By analyzing these metrics, you aim to provide actionable insights that will inform strategies to improve customer satisfaction and retention.

This problem will test your SQL or Python skills in:

  • Writing and optimizing code
  • Data analysis and manipulation
  • Real-world database scenarios used in Amazon interviews

What You'll Learn

By solving this Amazon interview question, you'll gain experience with:

  • Writing efficient SQL queries or Python code for production databases
  • Understanding complex data relationships and schema design
  • Applying SQL or Python (your choice!) in a Amazon-style technical interview setting
  • Problem-solving techniques used by data scientists and analysts at top tech companies

Getting Started

Use the code editor on the right to:

  1. Explore the database schema and table structures
  2. Write and test your SQL or Python (your choice!) queries in a real coding environment
  3. Get instant feedback on your query results
  4. Learn from hints and detailed explanations

Ready to practice this Amazon Data challenge? Let's dive in! 🚀

I'm ready to work on this Amazon interview problem. Can you break down the requirements for me?

Dawn AI

Excellent! Let's break down "Reorder Patterns for Amazon Fresh" step by step.

Problem Analysis

Company: Amazon
Problem Type: Data Science Interview Question
Skill Level: Professional interview preparation

Key Requirements

As a Data Analyst on the Amazon Fresh product team, you and your team are focused on enhancing the customer experience by streamlining the process for customers to reorder their favorite grocery items. Your goal is to identify the most frequently reordered product categories, understand customer preferences for these products, and calculate the average reorder frequency across categories. By analyzing these metrics, you aim to provide actionable insights that will inform strategies to improve customer satisfaction and retention.

Approach Strategy

For this Amazon interview question, consider:

  1. Data Exploration: Start by examining the table schemas to understand the data relationships
  2. Query Planning: Think about which tables you'll need to JOIN and what conditions to apply
  3. Code Optimization: Consider performance implications for large datasets (important for Amazon scale)
  4. Edge Cases: Think about NULL values, duplicate data, and boundary conditions

Next Steps

  1. Click on the "Schema" tab in the code editor to examine the table structures
  2. Review the sample data to understand the data patterns
  3. Start with a basic SELECT statement and build complexity gradually
  4. Test your query and iterate based on the results

This type of problem is commonly asked in Amazon technical interviews for data analyst, data scientist, and software engineer positions. Take your time to understand the problem thoroughly before writing your solution.

Ready to start coding? 💻

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Current Question

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The product team wants to analyze the most frequently reordered product categories. Can you provide a list of the product category codes (using first 3 letters of product code) and their reorder counts for Q4 2024?

Tables

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fct_orders (order_id, customer_id, product_id, reorder_flag, order_date)
dim_products (product_id, product_code, category)
dim_customers (customer_id, customer_name)
Ready to start practicing?