Netflix's global subscriber base has reached an impressive milestone, surpassing *** million paid subscribers worldwide in the fourth quarter of 2024. This marks a significant increase of nearly ** million subscribers compared to the previous quarter, solidifying Netflix's position as a dominant force in the streaming industry. Adapting to customer losses Netflix's growth has not always been consistent. During the first half of 2022, the streaming giant lost over *** million customers. In response to these losses, Netflix introduced an ad-supported tier in November of that same year. This strategic move has paid off, with the lower-cost plan attracting ** million monthly active users globally by November 2024, demonstrating Netflix's ability to adapt to changing market conditions and consumer preferences. Global expansion Netflix continues to focus on international markets, with a forecast suggesting that the Asia Pacific region is expected to see the most substantial growth in the upcoming years, potentially reaching around **** million subscribers by 2029. To correspond to the needs of the non-American target group, the company has heavily invested in international content in recent years, with Korean, Spanish, and Japanese being the most watched non-English content languages on the platform.

This dataset, titled "Netflix Stock Data and Key Affiliated Companies", provides comprehensive insights into the stock performance of Netflix (NFLX) alongside several key companies that have played a significant role in Netflix's growth and operational success. These companies include major technology and media giants such as Amazon (AMZN), Intel (INTC), Warner Bros. Discovery (WBD), Sony (SONY), and others.

Dataset Overview:

The dataset includes daily stock data for Netflix and a selection of companies that contribute to its content distribution, technological infrastructure, cloud services, and content licensing. The selection of affiliated companies highlights the broad ecosystem of services and technologies that power Netflix's streaming service and its original content production.

Key Companies Included:

1. Netflix (NFLX) – The leading global streaming platform that revolutionized the way we consume media.
2. Amazon (AMZN) – Provides critical cloud infrastructure via Amazon Web Services (AWS), enabling Netflix to scale globally.
3. Intel (INTC) – Supplies advanced processors and server technologies that help Netflix handle massive data loads.
4. Akamai Technologies (AKAM) – A key content delivery network (CDN) provider that ensures fast and reliable streaming.
5. Warner Bros. Discovery (WBD), Paramount Global (PARA), and Sony (SONY) – These media companies have been essential content partners for licensing and streaming rights, fueling Netflix’s growth before and during its original content development.

Features:

• Daily stock prices for Netflix and its key partners over time.
• Open, High, Low, Close, Volume and other financial metrics for each company.
• The dataset allows users to analyze correlations between Netflix and companies that provide essential services like cloud infrastructure, content delivery, and licensed content.

Use Cases:

• Financial Analysis: Evaluate stock trends, price movements, and performance relationships among Netflix and its affiliated companies.
• Business Strategy: Understand how various partnerships and technological dependencies have influenced Netflix’s rapid growth.
• Machine Learning: Use the data for stock prediction models, time-series analysis, or risk assessments by understanding the historical volatility of these companies.

Potential Analysis:

• Stock Price Correlation: Investigate the correlation between Netflix’s stock and its key partners, such as Amazon and Intel.
• Impact of Technological Partners: Assess the importance of key tech partnerships in supporting Netflix’s streaming infrastructure and business operations.
• Influence of Media Partnerships: Examine how the stock performance of media companies like Warner Bros., Sony, and Paramount align with Netflix’s success.

Conclusion:

By analyzing the historical stock data of Netflix alongside these affiliated companies, users can gain deeper insights into how a diverse set of industries—including technology, media, and cloud infrastructure—come together to create the backbone of Netflix’s success. This dataset serves as a valuable resource for financial analysts, machine learning enthusiasts, and business strategists interested in the interconnections between these influential companies.

How to Use:

• Download the dataset, and explore the stock data for the companies mentioned.
• Perform exploratory data analysis (EDA), build models to predict stock prices, or conduct business analysis to uncover the relationships that drive Netflix’s market success.

This dataset provides a solid foundation for understanding the financial landscape surrounding Netflix and its key partners.

Employment data for Netflix revealed that roughly 29 percent of Netflix's employees in the United States as of 2023 were Asian, and over 12 percent were Hispanic. The majority of employees working for the streaming giant are white.

In this post, you'll see how the Netflix platform is evolving, how many users Netflix has and how they perform against the growing competition.

Netflix reported a net income of over 1.8 billion U.S. dollars in the fourth quarter of 2024, around double the amount recorded a year earlier. Its revenue and subscriber base also increased and even beat expectations. Netflix’s profit compared to other DTC businesses Despite Netflix recording the highest expenses among major streaming services worldwide, it is one of the very few companies in the direct-to-consumer streaming business making money. In 2023, the operating profit of Netflix amounted to around seven billion U.S. dollars, while Paramount, for example, reported DTC losses of nearly two billion U.S. dollars that year. Disney’s losses exceeded two billion U.S. dollars. Netflix’s content expenditure flattens However, like other providers, the streaming giant implemented several measures to reduce churn and costs. For example, Netflix’s content spending will probably not continue to increase, but will remain stable in the years ahead. The company already abruptly stopped further production of TV series seasons like “That '90s Show” and “Unstable,” as high production costs failed to pay off and the shows were met with unsatisfied viewers.

Industry data revealed that Slovakia had the most extensive Netflix media library worldwide as of July 2024, with over 8,500 titles available on the platform. Interestingly, the top 10 ranking was spearheaded by European countries. Where do you get the most bang for your Netflix buck? In February 2024, Liechtenstein and Switzerland were the countries with the most expensive Netflix subscription rates. Viewers had to pay around 21.19 U.S. dollars per month for a standard subscription. Subscribers in these countries could choose from between around 6,500 and 6,900 titles. On the other end of the spectrum, Pakistan, Egypt, and Nigeria are some of the countries with the cheapest Netflix subscription costs at around 2.90 to 4.65 U.S. dollars per month. Popular content on Netflix While viewing preferences can differ across countries and regions, some titles have proven particularly popular with international audiences. As of mid-2024, "Red Notice" and "Don't Look Up" were the most popular English-language movies on Netflix, with over 230 million views in its first 91 days available on the platform. Meanwhile, "Troll" ranks first among the top non-English language Netflix movies of all time. The monster film has amassed 103 million views on Netflix, making it the most successful Norwegian-language film on the platform to date.

Analysis of ‘1000 Netflix Shows’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/chasewillden/netflix-shows on 21 November 2021.

--- Dataset description provided by original source is as follows ---

Context

Netflix in the past 5-10 years has captured a large populate of viewers. With more viewers, there most likely an increase of show variety. However, do people understand the distribution of ratings on Netflix shows?

Content

Because of the vast amount of time it would take to gather 1,000 shows one by one, the gathering method took advantage of the Netflix’s suggestion engine. The suggestion engine recommends shows similar to the selected show. As part of this data set, I took 4 videos from 4 ratings (totaling 16 unique shows), then pulled 53 suggested shows per video. The ratings include: G, PG, TV-14, TV-MA. I chose not to pull from every rating (e.g. TV-G, TV-Y, etc.).

Acknowledgements

The data set and the research article can be found at The Concept Center

Inspiration

I was watching Netflix with my wife and we asked ourselves, why are there so many R and TV-MA rating shows?

--- Original source retains full ownership of the source dataset ---

In 2023, Netflix reportedly had an almost equal share of male and female employees working for the company worldwide. The employees were reported as 51.6 percent female and 45.8 percent male, with 1.4 percent recorded as additional gender identities.

This dataset was constructed to support participants in the Netflix Prize. See [Web Link] for details about the prize.

There are over 480,000 customers in the dataset, each identified by a unique integer id.

The title and release year for each movie is also provided. There are over 17,000 movies in the dataset, each identified by a unique integer id.

The dataset contains over 100 million ratings. The ratings were collected between October 1998 and December 2005 and reflect the distribution of all ratings received during this period. Each rating has a customer id, a movie id, the date of the rating, and the value of the rating.

As part of the original Netflix Prize a set of ratings was identified whose rating values were not provided in the original dataset. The object of the Prize was to accurately predict the ratings from this 'qualifying' set. These missing ratings are now available in the grand_prize.tar.gz dataset file.

In 2024, Netflix revealed that it had 89.63 million paying streaming subscribers in the United States and Canada. North America had long been Netflix's biggest market, though subscriber numbers in the EMEA region surpassed that in the U.S. and Canada for the first time during 2022. The number of paid streaming memberships in Asia Pacific grew the most, by 13 percent compared with the previous year.

I extracted this data to find the unpopular movies on Netflix. The dataset I used here comes directly from Netflix movies data, which consists of 4 text data files, each file contains over 20M rows, over 4K movies, and 400K, customers. Altogether over are 17K movies and 500K+ customers!

I made some modifications and I extracted the e df_avgRating_with_usersCount.csv from the original data after applying some mathematical operations to get the average ratings and the count of users who made the ratings for each movie in movie_id below. Feel free to browse and use the data within your notebooks.

Here you could find my previous notebook on Kaggle to extract the dataset

The Netflix Prize was a competition devised by Netflix to improve the accuracy of its recommendation system. To facilitate this Netflix released real ratings about movies from the users (voters) of the system. Any set of movies can be transformed into an election via a process outlined by Mattei, Forshee, and Goldsmith.This data set includes all 5 candidate elections with at least 350 voters generated by this process from 300 randomly chosen movies. Extending beyond prior work by Mattei et al. we allow for weak preferences, i.e., a voter is indifferent between a set of movies if he assigns the same rating to each of them. Thus, there are 541 possibilities to rank a given set of five movies.The archive is gzip compressed and includes 165,672 elections in PrefLib.org's TOC file format (Orders with Ties - Complete List).

Context

This dataset contains OTT + Video Streaming Platforms - Revenue and User Stats 2011-21

Project / Tasks

• Time Series Analysis.
• Market Analysis.
• Analysis and predict future.
• Find patterns.

https://empireweekly.com/wp-content/uploads/2022/01/fortuneindia_2020-11_9cc704de-6f70-4a3f-b3e2-92991dfb24e3_netflix.jpeg" alt="">

About OTT, Video Streaming Platforms

OTT stands for “over-the-top,” which refers to any TV or video content that's streamed over the internet. This includes any web or app-based streaming service, like Netflix, YouTube, Disney Plus and many more. There's a wide range of OTT platforms, including Netflix, Disney+, Hulu, Amazon Prime Video, Hulu, Peacock, CuriosityStream, Pluto TV, and so many more. Unlike OTT platforms, YouTube is a social video platform that was originally designed to allow everyday consumers to share moments caught on video. YouTube has attempted to enter the OTT market a number of times with limited success, since the market clearly sees YouTube as a place for free content.

Content

| | File | File Type | | -- | ---------------------------- | --------- | | 1 | LibrarySize.csv | CSV file | | 2 | MinuteSharing.csv | CSV file | | 3 | AppUsage.csv | CSV file | | 4 | NumSubscribers.csv | CSV file | | 5 | Revenue.csv | CSV file | | 6 | Revenue.csv | CSV file | | 7 | AdRevenue.csv | CSV file | | 8 | LiveTVSubscribers.csv | CSV file | | 9 | NumSubscribers.csv | CSV file | | 10 | Profit.csv | CSV file | | 11 | Revenue.csv | CSV file | | 12 | SubscriptionRevenue.csv | CSV file | | 13 | Valuation.csv | CSV file | | 14 | ContentSpend.csv | CSV file | | 15 | NumSubscribers.csv | CSV file | | 16 | NumSubscribersByRegion.csv | CSV file | | 17 | Profit.csv | CSV file | | 18 | Revenue.csv | CSV file | | 19 | RevenueByRegion.csv | CSV file | | 20 | Revenue.csv | CSV file | | 21 | Users.csv | CSV file | | 22 | AdRevenue.csv | CSV file | | 23 | ConcurrentViewers.csv | CSV file | | 24 | HoursWatched.csv | CSV file | | 25 | MostViewedGamesOnTwitch.csv | CSV file | | 26 | Revenue.csv | CSV file | | 27 | TwitchAgeDemographics.csv | CSV file | | 28 | TwitchGenderDemographics.csv | CSV file | | 29 | TwitchStreamers.csv | CSV file | | 30 | AppUsage.csv | CSV file | | 31 | NumSubscribers.csv | CSV file | | 32 | Revenue.csv | CSV file | | 33 | AppUsage.csv | CSV file | | 34 | NumSubscribers.csv | CSV file | | 35 | Revenue.csv | CSV file | | 36 | TopPlatforms.csv | CSV file | | 37 | PremiumSubscribers.csv | CSV file | | 38 | Revenue.csv | CSV file | | 39 | Users.csv | CSV file |

Download

• kaggle API Command !kaggle datasets download -d azminetoushikwasi/ott-video-streaming-platforms-revenue-and-users

Disclaimer

• The data collected are all publicly available and it's intended for educational purposes only.

Acknowledgement

• Cover image taken from internet.

Appreciate, Support, Share

Analysis of ‘FAANG- Complete Stock Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/aayushmishra1512/faang-complete-stock-data on 30 September 2021.

--- Dataset description provided by original source is as follows ---

Context

There are a few companies that are considered to be revolutionary. These companies also happen to be a dream place to work at for many many people across the world. These companies include - Facebook,Amazon,Apple,Netflix and Google also known as FAANG! These companies make ton of money and they help others too by giving them a chance to invest in the companies via stocks and shares. This data wass made targeting these stock prices.

Content

The data contains information such as opening price of a stock, closing price, how much of these stocks were sold and many more things. There are 5 different CSV files in the data for each company.

--- Original source retains full ownership of the source dataset ---

Netflix is currently facing the challenge of retaining subscribers worldwide, with data from the second quarter of 2023 revealing that Germany and Spain experienced the highest churn rates at **** percent. Australia followed closely, while France had a relatively low cancellation rate at just *** percent. Impact of the new business model The subscription video-on-demand (SVOD) market has experienced a significant increase in the past decade, driven by major players, like Netflix, Amazon Prime Video, and Disney+. However, the anticipated slowdown in revenue growth, coupled with the increasing popularity of ad-supported content and subscription cycling, underscores the evolving dynamics of consumer preferences within the streaming industry. Netflix's introduction of a basic plan served with commercials in late 2022 had a significant impact on subscriber behavior in the U.S., with the ad-supported tier accounting for ** percent of sign-ups in September 2023. Growth despite challenges Netflix's global position remains strong. With over *** million paid subscribers worldwide, the company's revenue continues to grow, reaching nearly *** billion U.S. dollars in the first quarter of 2024. While challenges persist, such as the increasing popularity of other streaming services and the impact of price increases on subscriber numbers, Netflix's plan to generate revenue from sources, like licensing, ads, and merchandise, positions the company for future profitability.

In the first quarter of 2025, revenues of Amazon Web Services (AWS) rose to 17 percent, a decrease from the previous three quarters. AWS is one of Amazon’s strongest revenue segments, generating over 115 billion U.S. dollars in 2024 net sales, up from 105 billion U.S. dollars in 2023. Amazon Web Services Amazon Web Services (AWS) provides on-demand cloud platforms and APIs through a pay-as-you-go-model to customers. AWS launched in 2002 providing general services and tools and produced its first cloud products in 2006. Today, more than 175 different cloud services for a variety of technologies and industries are released already. AWS ranks as one of the most popular public cloud infrastructure and platform services running applications worldwide in 2020, ahead of Microsoft Azure and Google cloud services. Cloud computing Cloud computing is essentially the delivery of online computing services to customers. As enterprises continually migrate their applications and data to the cloud instead of storing it on local machines, it becomes possible to access resources from different locations. Some of the key services of the AWS ecosystem for cloud applications include storage, database, security tools, and management tools. AWS is among the most popular cloud providers Some of the largest globally operating enterprises use AWS for their cloud services, including Netflix, BBC, and Baidu. Accordingly, AWS is one of the leading cloud providers in the global cloud market. Due to its continuously expanding portfolio of services and deepening of expertise, the company continues to be not only an important cloud service provider but also a business partner.