Building data infrastructure

Learn how to build robust data pipelines for basketball analytics, from data collection to storage and processing. This topic covers ETL processes, data validation, scheduling automated jobs, and creating scalable infrastructure for handling large volumes of NBA data. You'll learn best practices for data pipeline architecture and how to handle common challenges like API rate limits and data inconsistencies.