Netflix is a name everyone knows by heart, but it wasn’t this popular when it started. The secret behind the success of Netflix is Big Data.
Today, Netflix has a massive user base exceeding 140 million. It aims to give its users a personalized experience with the help of data gathered.
Netflix has deployed several algorithms and mechanisms to help steer the company in the right direction.
- Near Real-Time Recommendation engine: Based on what a user watches throughout the day, Netflix uses machine learning algorithms to understand the viewer’s taste.
- Artwork & Imagery Selection: Netflix uses a tool called Aesthetics Visual Analytics (AVA), an algorithm that selects what artwork and images to show to which group of users based on their likings.
- Production Planning: Big Data plays a huge role in creating new and original content based on the viewer’s response to prior content. Predictive models can save a significant amount of effort put into planning.
- Metaflow: Netflix has open sourced Metaflow to shift the focus if data scientists from worrying about the infrastructure of models to solving problems.
- Polynote: Netflix developed and opened sourced Polynote, which allows smooth integration of the JVM based ML platform.
- Metacat: Netflix introduced Metacat to maintain seamless interoperability among all data stores.
- Druid: Netflix uses Apache Druid, a high-performance real-time analytics database, to give its users a high-quality user experience every time.
- Use of Python: Netflix uses Python for managing aspects like applications managing the CDN infrastructure, analyzing data, prototyping visualization tools, maintaining security, etc.
Big data doesn’t just help Netflix function but presents them with new opportunities to grow.
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