Design the data pipeline for a personalization model

Focus on outlining the key components of the data pipeline, including data ingestion, processing, storage, and model training. Explain how you would handle real-time versus batch data processing, and consider the types of data sources you would integrate (e.g., user behavior, demographics, and external data). Discuss the tools and technologies you would use for each stage, such as ETL frameworks, databases, and machine learning platforms. Be prepared to address data quality, scalability, and how you would ensure the model remains up-to-date with evolving user preferences.