Enhancing Recommender Engines with New Data Features

As an AI product manager, enhancing a recommender system involves incorporating more data for accurate recommendations. This can be achieved by tapping into additional data sources like weather APIs or event calendars using tools like Airbyte. However, it's crucial to ensure the quality of the data to avoid "Garbage In, Garbage Out" situations. Incorporating new data features from external sources can significantly improve recommender engine performance, especially in handling predictable events such as seasonal changes or weather-related trends.