NETFLIX: CHANGE THE GAME WITH BIG DATA

Netflix is a streaming service that offers a wide variety of award-winning TV shows, movies, anime, documentaries, and more on thousands of internet-connected devices. One of the main advantages that Netflix has is its technology. Especially their recommendation system. From 2012 onwards, Reed Hastings and Marc Randolph using big data to filter their user information, which removes unnecessary information from the data stream before it reaches users. Netflix offers a recommendation system that can make it easier for users to watch. Users can easily find movies or series with the type of genre or other things they like through the recommendation system offered. This is one of Netflix’s ways to satisfy and gain its users.

In 2020 Netflix was able to gain 18.2 million new users. During the pandemic, many people use Netflix to deal with boredom and stress. So it became one of the factors that increased Netflix during the pandemic. However, the recommendation system also has a significant impact on Netflix. The recommendation system provides users with a sense of comfort and convenience. Customers can quickly determine which movies or series to watch according to their preferences.

The use of big data is obtained from customer history using Netflix. The weak point of big data is that there may be an excessive amount of data to process so sometimes inaccuracies are found in the recommendation system. According to this matter, Netflix tries to overcome this by dividing the task to its researchers (Exhibit 1) based on their problem solving skills. So that in using big data which is more consumer centric, Netflix hopes to improve and provide better services or products to its users.