Netflix and Data Science Project Report: Student Analysis and Insights

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This report provides a detailed analysis of how Netflix utilizes data science to enhance its streaming services. It begins with an introduction to Netflix and its business model, emphasizing its reliance on data science for movie recommendations and content management. The report explores the various data roles within Netflix, including data analysts, data scientists, machine learning engineers, and data engineers, outlining their responsibilities and contributions. It then delves into the characterization of Netflix's data, including data types, storage methods, and processing times, highlighting the use of cloud storage and ETL processes. The report examines Netflix's data analysis techniques, focusing on how the company collects and analyzes user data to discover customer behavior and preferences, with a specific mention of the inferential statistical methods used. Furthermore, it discusses Netflix's data management strategies, including how user data is utilized for quality control and personalized recommendations. Finally, the report concludes by summarizing the key resources, data analysis methods, and overall data-driven approach that enables Netflix to provide an optimal user experience.
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Running head: NETFLIX AND DATA SCIENCE 1
Netflix and Data Science
Student
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Institutional Affiliations
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NETFLIX AND DATA SCIENCE 2
PROJECT INFORMATION
Introduction
Recommender systems are common in e-commerce organizations, content based
websites. It involves a technology used to analyze data in order to make suggestions for what
may interest users such as videos, books and many others. Netflix is one of the organizations that
use recommender system to recommend videos to its users. This report discuss Netflix
recommender system by examining how the organization use data science to manage the massive
data it holds to serve its users.
What is Netflix?
Netflix is one of the most popular online subscription platform offering television shows
and movies to its customers through mail or by direct streaming from their websites (Netflix,
2019). They provide their customers with unlimited access to their voluminous video library.
The organization provide a wide ranging content across almost all genre one can imagine. This is
provided through streaming service where one can watch videos as such, movies, television
shows well as documentaries by subscribing and streaming using data to access the internet.
Relation to data science
The organization initially started as a DVD retail service provider back in the year 1998.
For its business, they majorly relied on the third party postal services to serve their customers
which did not show some efficiency which the organization mitigated soon with the use of data
science. Netflix apply data science in various ways, however, for this assignment, we focus on
recommender system.
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NETFLIX AND DATA SCIENCE 3
Movie recommendation:
The recommendation system easily identify users’ needs and offer suggestions of various
video products to the Netflix users. This is achieved by use of watching history of their
customers with alike tastes for recommending what their customers would be most interested in
watching next time so that they engage them and continue subscribing for more shows.
The recommender system employs various technology and methodologies in filtering
massive data and provide a smaller amount of the data for users to suggest the ones that fulfill
their interest. In Netflix, Meta data tagging is used in videos along with the data about the
behavior of Netflix users in order to come up with recommended videos as well as TV shows for
specific users.
As shown, the concepts in Data Science are applied by Netflix in a number of ways, other
ways include uploading and storage of wide global content library as well as monthly, weekly,
and daily updates on video content. Furthermore, they allow real-time access wit content that
vary with regions together with showing different standards of videos as such, Standard
Definition, High Definition and Ultra High Definition.
Data Roles
By looking at the Podcast for Data Engineering on
(https://www.dataengineeringpodcast.com/using-notebooks-as-the-unifying-layer-for-data-roles-
at-netflix-with-matthew-seal-episode-54/), we can conclude that there are many data roles
practiced in Netflix Company. Data Analytics: Involves an analyst collecting and storing data
and information of behaviors (Waller & Fawcett, 2013). They have expertise that ensure data
accuracy and process it as well presenting it in a way that can be meaningful.
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Data Algorithms: It involves data mining and use of data analysis methods. They build
and implement models as well as creating simulations.
Data scientist
A data scientist at Netflix company is a person that is able to utilize technological skills
that are related to science and engineering with an aim of achieving analytics.
Data analyst
Netflix Company’s data analyst is an individual who analyses data with an aim achieving
some insights. These insights are then transmitted to the management of the company for making
of decisions. Therefore, as a data analyst at this organization a person should be able to examine
data at all levels be it those from reports or databases.
Machine learning engineer
This is a person that owns a degree in machine learning or related field. This person
should be able to use skills of machine learning to a widespread dataset. Also, he/she should
come up with solutions that can create a strong user base of Netflix Company.
Data engineer
Data engineer should have an ability of working in partnership with other personnel team
so that they can create test solutions
BUSINESS MODEL
With much revolution in the industry, there is rise in number of internet users who search
for streaming services. It is important to note that, even such services came to existence; people
opted for CDs and bought films and videos from video shops. Netflix utilized the rate of mobile
acquisition and use of internet to provide the services. Thus they provided the internet users with
relevant and their desired videos, films, documentaries and TV shows.
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Netflix’s success solely depends on some of the aspects namely: the capability to ensure
updated categories of videos through analysis of users’ demand and existing up-time search
engine optimization (SEO).
The organization makes use of a subscription based business model. Initially, they have
been using a business model which is quite similar to the brick and mortar video rental store.
Netflix is exploring the change in the way it provides services to its consumers from DVDs to
online streaming and it is now turning to a global television network. The organization buy
products from product creators and distributes the products to its subscribers through internet
There are many individuals who like videos have been trying very hard to get the best.
Therefore, Netflix Company has provided the best platform for providing these videos. This
organization has television network that offers streaming service through subscriptions that allow
their customers to watch a large number of documentaries, movies and series.
Data specific
By basing on the dimension of provision of videos the effectiveness of Netflix company
depends on several aspects:
Provision of videos in searchable way
Provision of rating to videos
CHARACTERISING THE DATA AND DATA PROCESSING
Data types
Netflix has various data in its store. The following shows the data types in the
organization. The data types are divided into two, firstly the actual films and movies types that
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NETFLIX AND DATA SCIENCE 6
users want to view. This they can stream live or download on their devices. The TV shows and
Documentaries are also featured in Netflix. They include award winning shows and many more.
Videos and movies: these are product files supplied to the organization’s subscribers
Customer feedback and interaction data: these include user response, time and dates users
watch as well as the device used.
Netflix Company has kept in their database more than eight thousand TV shows and
movies. It has 2 types of data storage; Flash drive and a hundred terabyte hard drive (McCord,
2014). The main challenge that they encountered is coming up with a readily available storage
technique that would keep their data for long. Cloud storage was adopted as its remedy.
Reaching customers
Netflix Company allows their users to subscribe so that they can access the content of
choice that have been arranged in libraries.
Processing times
Netflix company process data in two ways; periodic and real time. This data processing is
achieved by Aesthetic Visual Analysis (AVA) technology.
Membership Plans
Netflix provides three membership plans namely, the Basic Plan which screen plays the
Standard Definition content, and the Standard Plan which screenplays the High Definition
content and finally, the Premium Plan which screenplays the Ultra High Definition.
Data storage and volume
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Netflix organization have storage servers made of a combination of hard drives which are
combined together in a server. The organization currently uses 36 drivers which holds
approximately 100 tetra bites of data. The servers can store and stream approximately 15,000
movies simultaneously and they have almost thousands of data stations spread around the world
where contents get collected after which they are spread to various places around the world. The
volume of data held by Netflix requires to be organized and shifted. Thus during the off hours,
the organization always fill the servers with movies and shows which are most popular in order
to reduce the band width during high seasons.
Netflix data handling technology layer is called Extra Transform and Load ETL. This
approach include the process of managing big data where methodologies which take into account
features including quality are used. By this, the data which are useful to the organization are used
as it is rarely associated with errors and it corresponds to the business goals of the organization.
Data loading process
The data loading process is outlined within the data plan. It outlays facets like data storage and
data management models which are always available in two options including: cloud storage and
big data repository i.e. data warehouse.
Netflix data analytical layer
This is the process that the organization executes once the data is ready i.e. once the
massive data that is needed by the organization is ready. The process provide the previously
established performance metrics. They have a catalog which relies on complex algorithms for
monitoring its subscribers online which also aims at formalizing the satisfactory decisions
regarding views.
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RESOURCES
Netflix has numerous resources. The following shows the organization’s key resources.
Its first key resource is the massive inventory of DVDs. Another key resource is the rights owned
by the organization to stream content to its users. The organization is capable of offering a
multitudinous content to its user; the organization has deals with more content producers.
Netflix platform is also another key assets owned by the organization. The organization
has invested a great deal in the platform to ensure that it is favorable for its subscribers as it offer
a wide ranging developed features like shows and Movies recommendations.
The 1000 data stations through which response from its users as well as its users
interactions are collected for further data analysis is another key resource owned by Netflix. This
system provides the Netflix users with their preferences based on what they like. This involves
the information from the user used as data input that is processed and later used as a prediction.
This system depends on the efficiency of the Machine Learning Algorithms. Entirely, this system
ensures personalization of the users wants is upheld as those seeking streaming services want a
user-friendly internet platform with little mishaps.
DATA ANALYSIS
Netflix collects data from its users and then then apply the data analytics model to
discover behavior of its customers as well as their buying pattern. They then use this data in
recommending movies and TV shows according to their subscribers’ preference.
As reported by Netflix, more than 75 percent of its subscribers activities are based on the
personalized and recommendation. The organization harvest many data points to create a
detailed profile for its users. Essentially, Netflix collects its user’s response to TV shows and
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NETFLIX AND DATA SCIENCE 9
interaction data. For instance, the organization knows the time its users and the categories of
shows they watch.
Statistical method
Inferential method was used in this project. This method allowed use of different
information for making conclusions. This technique was important since it made it possible to
provide exact programs.
High level output
High level output was achieved in this project by using different sources for generation of facts.
DATA MANAGEMENT
The over 100 million Netflix users across the world represent more than 150 million view
hours in a day. The view hours consumed by use of devices connected to the internet is related to
the users’ data batches which the organization control and utilize in order to understand what its
users need and find out its goals. These enable the organization to come up with a data
management strategy as defined by their aspirations.
What does Netflix use its consumers’ data for?
Netflix, unlike google or other adverts driven organizations does not use its user’s data to
negotiate with media organizations or advertisers to generate its revenue. Rather, the subscribers’
data in the organization serves various reasons stated as follows.
i. Netflix uses its users’ data for the quality control of the acquired rights.
ii. These data offer the organization the chances to provide its users with more personalized
recommendations in order to help them to select their desired content without getting
overwhelmed the catalog’s size.
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NETFLIX AND DATA SCIENCE 10
iii. These data helps to ensure an optimal catalog. As explained by Netflix, the organization
have no aspiration to have it all, but rather to ensure that their customers are satisfied by
their services thus the non-renewal titles which are much popular among its subscribers.
iv. These data also help the organization to generate contents with their subscribers’
presences taken into account.
The data analysis that help the organization to know its customers is the organization’s strategic
key that ensure the success of Netflix services.
How does Netflix select their data sources?
Netflix’s business goals lies on the choice of their data sources. The organization’s data
source could be defined by the data that their users provide themselves through their website.
This is service which involve an internet connected devices to enable the significant number of
interaction, data collection and the possibilities of convergence.
According to the organization’s statistics, an average subscriber one to two minutes to
decide a show or movie to watch after which the chances of viewing other contents are
significantly reduced. This helps in gaining insights into understanding monitoring that the
organization does on the habits of its subscribers in relation to the contents viewed or discarded;
content playback characteristics; the type of the device used to gain access into the system; the
ratings given to a contend by users; and playback intensities. This also helps in keeping the path
traced by users like time, geographical locations, searches as well as the page where content was
found by the customer and the recommendations discarded.
The organization is determined to focus its business model on the technical view quality
demand and the capacity of contents accessibility. This is the reason why Netflix evaluates each
playback’s technological state such as how the personalized recommendations can be enabled,
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how transmission speed and content storage impact subscribers’ behavior as well as how they
can improve content delivery.
The data is then crossed with other metadata that are assigned by the organization to the
contents it provide for its users encompassing both artistic, technical content and many others.
This enables the organization to identify the extent to which understanding the clients is related
to the high rate of the use of a service. The information that are usually provided by the users i.e.
ratings and response among others are used as references while comparing them with the data
obtained in a voluntary manner. The mode of monitoring that occur within the client’s own
environment and that is not perceived by any device connection leads to access to more valuable
unconditioned results that allow the organization to collect all the information related to what
motivates them to watch some contents.
Methods in data analytics
Big data analytics involves the process of examining a large volume and varied data sets.
The larger the volume of the data, the more accurate result the recommendation system provide.
Thus Netflix utilize the huge data it has to recommend videos to its clients for competitive
advantage reasons. Organizations use various strategies to examine the data sets from their
clients. With the extensive data available due to technological innovation. The organization
sought to implement data analytics method that would work fast to ensure that all its users are
served. There are various methods that could be utilized by the organization. However, the
method chosen simply depends on the type, characteristics and the quantity of data. In this
section, we will discuss the methods used by Netflix to recommend videos to its users.
One of the basic method is editorial where the platform would make recommendation on
basis of a small amount of data that are available. There is also simple collection method were
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selections are made on basis of the top products across the platform. However, these methods are
only efficient with small amounts of data. Moreover, the recommendation methods does not
enable personalization, they neither cover the breadth of Netflix users’ preferences and movie
catalogs. Since Netflix holds massive data, the organization employs new equipment and
methodologies intended to help its data engineers to analyze these huge amounts of data.
The organization instead employs a personalized method which suggests movies based
on the likelihood of that user to watch the movie based on movie type and characters in the
movie. The organization employs machine learning for this method due to the reason that the
data about the behavior of users is used in making suggestions here. Thus this strategy accounts
for the enormous Netflix users as well as the organization’s catalog. The organization applies
estimations and probability which is the capability of machine learning in order to identify the
chances that the user will like a certain content. For instance, if a given user has watched some
movies previously in the organizations online catalog and provide a rating for that particular
movie, Netflix determines the relationship between the user and the movie such that if the ratings
are good, Netflix recommendation machine suggest the same kind of movie to its users.
Security and Privacy
In this organization they have policies that regulate access of location, photos and mobile
numbers. The organization has implemented some of the world’s best information security
management system that assure security and privacy to its users. Moreover, Netflix
organization’s CEO announced in a quarterly report that their online streaming will get far more
security. As stated by the company’s CEO, Netflix has evolve from using the usual HTTP to the
use of the HTTPS, a more secure method, while streaming on the organization websites
(Armasu, 2016).
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