Fan Engagement Metrics for Sports Coverage

Company:X
Dawn AI

Welcome to Interview Master! 👋

I'm here to help you practice Fan Engagement Metrics for Sports Coverage - a Data interview question from X.

Problem Overview

As a Product Analyst for the X sports updates platform, your team is focused on enhancing user engagement with live sports content. You need to analyze user interactions with both live sports commentary and highlights to identify patterns and preferences. The insights will help prioritize content strategies and improve the user experience during live events.

This problem will test your SQL or Python skills in:

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

What You'll Learn

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

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

Dawn AI

Excellent! Let's break down "Fan Engagement Metrics for Sports Coverage" step by step.

Problem Analysis

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

Key Requirements

As a Product Analyst for the X sports updates platform, your team is focused on enhancing user engagement with live sports content. You need to analyze user interactions with both live sports commentary and highlights to identify patterns and preferences. The insights will help prioritize content strategies and improve the user experience during live events.

Approach Strategy

For this X 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 X 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 X 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? 💻

Interview Master can make mistakes. If you encounter a mistake

Current Question

1
2
3
What is the average duration of user interactions with live sports commentary during April 2024? Round the result to the nearest whole number.

Tables

?
fct_user_interactions (interaction_id, user_id, content_type, interaction_duration, interaction_date, category_id)
dim_sports_categories (category_id, category_name)
Ready to start practicing?