Magna Notitia

  Netflix services fall under the subscription video-on-demand (SVOD) services category as a so called over-the-top (OTT) provider, which streams content over the web directly to its customers’ devices (Iordache et al., 2021; Pajkovic, 2021). Netflix’s revenue is mainly generated by users’ subscription fees (Kasula, 2020), and to keep customers from cancelling their access, the company relies heavily on the Netflix Recommender System (NRS) which combines big data analytics with powerful machine learning (ML) algorithms (Jackman & Reddy, 2020; Pajkovic, 2021) to keep users engaged and satisfied with the service.  The aim of the NRS is to offer a personalized experience and provide viewing recommendations to each customer (Pajkovic, 2021) based on preferences generated by their rating history (rating the titles they watch), Netflix’s requests for feedback, a “similarity” approach across subscribers, movies, genres, etc. (Kasula, 2020). The NRS is driven by powerful machine l...

  New, innovative, and more efficient technologies have enabled the management of big data for analytics to extract meaningful insights for decision-making (Minelli et al., 2013), emphasize the many differences between big data and conventional data.  Edd Dumbill as cited in Minelli et al. (2013), defines big data as “data that becomes large enough that it cannot be processed using conventional methods,” and Gartner’s definition in 2001 reads “Big data is data that contains greater variety arriving in increasing volumes and with ever-higher velocity” (Treehouse, 2022), featuring big data’s three V’s: variety, volume, and velocity (Minelli et al., 2013). Kumar et al. (2021) explains that with big data, it is possible to store large volumes of data, but not in a conventional data setup. Conventional data reflects a centralized database architecture, and big data is found in distributed databases. The data sources are many when dealing with big data, but severely limited with co...