Work Travel Expense Tracking and Optimization

Company:Airbnb
Dawn AI

Welcome to Interview Master! 👋

I'm here to help you practice Work Travel Expense Tracking and Optimization - a Data interview question from Airbnb.

Problem Overview

As a Business Analyst on the Airbnb for Work team, your task is to analyze corporate travel expense patterns to identify potential cost-saving opportunities. Your team is particularly interested in understanding the average booking costs, company-specific spending behaviors, and the impact of booking timing on costs. By analyzing these aspects, you aim to provide actionable insights that can help optimize corporate travel expenses.

This problem will test your SQL or Python skills in:

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

What You'll Learn

By solving this Airbnb 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 Airbnb-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 Airbnb Data challenge? Let's dive in! 🚀

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

Dawn AI

Excellent! Let's break down "Work Travel Expense Tracking and Optimization" step by step.

Problem Analysis

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

Key Requirements

As a Business Analyst on the Airbnb for Work team, your task is to analyze corporate travel expense patterns to identify potential cost-saving opportunities. Your team is particularly interested in understanding the average booking costs, company-specific spending behaviors, and the impact of booking timing on costs. By analyzing these aspects, you aim to provide actionable insights that can help optimize corporate travel expenses.

Approach Strategy

For this Airbnb 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 Airbnb 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 Airbnb 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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What is the average booking cost for corporate travelers? For this question, let's look only at trips which were booked in January 2024

Tables

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fct_corporate_bookings (booking_id, company_id, employee_id, booking_cost, booking_date, travel_date)
dim_companies (company_id, company_name)
Ready to start practicing?