Netflix Recommendation Engine
Netflix's recommendation engine is a complex system that uses a variety of technologies and techniques to provide personalised recommendations to users based on their viewing history and preferences. At a high level, the recommendation engine infrastructure consists of several key components: Data collection: Netflix collects data on user interactions with the platform, including what shows and movies they watch, how long they watch for, and what they rate and review. This data is used to create personalised recommendations for each user. Data storage: The data collected by Netflix is stored in a variety of data stores, including relational databases, NoSQL databases, and data warehouses. This allows for efficient querying and analysis of the data. Data processing: Netflix uses a variety of tools and technologies to process and analyze the data collected from user interactions. This includes using machine learning algorithms to identify patterns and trends in the data, as well as n