10 datasets found
  1. Global net revenue of Amazon 2014-2024, by product group

    • statista.com
    • ai-chatbox.pro
    Updated Feb 24, 2025
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    Statista (2025). Global net revenue of Amazon 2014-2024, by product group [Dataset]. https://www.statista.com/statistics/672747/amazons-consolidated-net-revenue-by-segment/
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    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    In 2024, Amazon's net revenue from subscription services segment amounted to 44.37 billion U.S. dollars. Subscription services include Amazon Prime, for which Amazon reported 200 million paying members worldwide at the end of 2020. The AWS category generated 107.56 billion U.S. dollars in annual sales. During the most recently reported fiscal year, the company’s net revenue amounted to 638 billion U.S. dollars. Amazon revenue segments Amazon is one of the biggest online companies worldwide. In 2019, the company’s revenue increased by 21 percent, compared to Google’s revenue growth during the same fiscal period, which was just 18 percent. The majority of Amazon’s net sales are generated through its North American business segment, which accounted for 236.3 billion U.S. dollars in 2020. The United States are the company’s leading market, followed by Germany and the United Kingdom. Business segment: Amazon Web Services Amazon Web Services, commonly referred to as AWS, is one of the strongest-growing business segments of Amazon. AWS is a cloud computing service that provides individuals, companies and governments with a wide range of computing, networking, storage, database, analytics and application services, among many others. As of the third quarter of 2020, AWS accounted for approximately 32 percent of the global cloud infrastructure services vendor market.

  2. Amazon revenue 2004-2024

    • statista.com
    Updated Jun 25, 2025
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    Statista (2025). Amazon revenue 2004-2024 [Dataset]. https://www.statista.com/statistics/266282/annual-net-revenue-of-amazoncom/
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    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States, Worldwide
    Description

    From 2004 to 2024, the net revenue of Amazon e-commerce and service sales has increased tremendously. In the fiscal year ending December 31, the multinational e-commerce company's net revenue was almost *** billion U.S. dollars, up from *** billion U.S. dollars in 2023.Amazon.com, a U.S. e-commerce company originally founded in 1994, is the world’s largest online retailer of books, clothing, electronics, music, and many more goods. As of 2024, the company generates the majority of it's net revenues through online retail product sales, followed by third-party retail seller services, cloud computing services, and retail subscription services including Amazon Prime. From seller to digital environment Through Amazon, consumers are able to purchase goods at a rather discounted price from both small and large companies as well as from other users. Both new and used goods are sold on the website. Due to the wide variety of goods available at prices which often undercut local brick-and-mortar retail offerings, Amazon has dominated the retailer market. As of 2024, Amazon’s brand worth amounts to over *** billion U.S. dollars, topping the likes of companies such as Walmart, Ikea, as well as digital competitors Alibaba and eBay. One of Amazon's first forays into the world of hardware was its e-reader Kindle, one of the most popular e-book readers worldwide. More recently, Amazon has also released several series of own-branded products and a voice-controlled virtual assistant, Alexa. Headquartered in North America Due to its location, Amazon offers more services in North America than worldwide. As a result, the majority of the company’s net revenue in 2023 was actually earned in the United States, Canada, and Mexico. In 2023, approximately *** billion U.S. dollars was earned in North America compared to only roughly *** billion U.S. dollars internationally.

  3. A

    ‘FAANG- Complete Stock Data’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Sep 20, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘FAANG- Complete Stock Data’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-faang-complete-stock-data-53b0/latest
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    Dataset updated
    Sep 20, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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 14 February 2022.

    --- 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 ---

  4. Sims 4 Data

    • kaggle.com
    Updated Mar 10, 2022
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    N White13 (2022). Sims 4 Data [Dataset]. https://www.kaggle.com/datasets/nwhite13/sims-4-data
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 10, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    N White13
    Description

    Context

    The Sims series has been around for over 20 years. Sims 4 is the latest iteration of the series and has been around since 2014. Since Sims 4 hasn't been met with uniform high praise, many fans have compared it to previous versions of the Sims especially Sims 2 and Sims 3. Many have discussed what was available and gameplay interactions in Sims 2 and Sims 3. This is why there is information about Sims 3 included in the dataset.

    Sims 4 has had quite a bit of controversy from its dedicated fans about paid-content add-ons that range from 5 USD to 40 USD. Much of the downloadable content (DLC) has been reviewed or discussed in the Sims community across the internet.

    Let's take a look at what is available in the DLC's available.

    Updates

    Planning monthly updates and to update when there are additional announcements about the Sims 4. Currently, patch data is not available in this dataset, nor is there much information about Sims 3 and Sims 4 Bundles. These will be updated.

    Content

    Collected information about the Sims 4 with its iterations and add-ons. Sims 4 Individual Packs follows the available Sims 4 pieces available on Origin - the official EA place to play the Sims 4. So far there are numerous add-ons and they continue to be released despite the Sims 4 coming out in 2014. (Official US PC release date is September 2, 2014)

    Release time is available for some DLC because of current anticipated releases or DLC already released.

    This data was collected from many sources including Origin, EA, Steam, SimsCommunity.info, SimsVIP, Carl's Sims 4 Guide, Sims.fandom.com, MetaCritic, Amazon, and more. This initial upload has some information about each available purchase of the Sims 4 and DLC including Release Date, Price, and some ratings.

    ** V1 Update: ** Included Sims 3 Data under Individual Packs for Title, Release Date, Steam Rating, and Price. Information will need to be moved around, but data is still useable. Information collected from Origin, Steam, and Sims.fandom.com .

    Acknowledgements

    Shoutout to all the dedicated Simmers who paid over $900 USD to play the Sims 4 with every add-on and DLC. Also to those who just play with custom content (like myself).

    Carl's Sims 4 Guides are a great place to get an understanding of the Sims 4 and they had a great collection of information about the Sims 4 on their website and YouTube channel.

    Inspiration

    I'd love to see someone decide which type of DLC is worth the money like a front-runner for kits, or stuff packs, or expansion packs.

  5. f

    Static analysis of Yelp and Amazon data sets.

    • figshare.com
    • plos.figshare.com
    xls
    Updated May 30, 2025
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    An Tong; Bochao Chen; Zhe Wang; Jiawei Gao; Chi Kin Lam (2025). Static analysis of Yelp and Amazon data sets. [Dataset]. http://doi.org/10.1371/journal.pone.0322004.t005
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    xlsAvailable download formats
    Dataset updated
    May 30, 2025
    Dataset provided by
    PLOS ONE
    Authors
    An Tong; Bochao Chen; Zhe Wang; Jiawei Gao; Chi Kin Lam
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In recent years, the number of telecom frauds has increased significantly, causing substantial losses to people’s daily lives. With technological advancements, telecom fraud methods have also become more sophisticated, making fraudsters harder to detect as they often imitate normal users and exhibit highly similar features. Traditional graph neural network (GNN) methods aggregate the features of neighboring nodes, which makes it difficult to distinguish between fraudsters and normal users when their features are highly similar. To address this issue, we proposed a spatio-temporal graph attention network (GDFGAT) with feature difference-based weight updates. We conducted comprehensive experiments on our method on a real telecom fraud dataset. Our method obtained an accuracy of 93.28%, f1 score of 92.08%, precision rate of 93.51%, recall rate of 90.97%, and AUC value of 94.53%. The results showed that our method (GDFGAT) is better than the classical method, the latest methods and the baseline model in many metrics; each metric improved by nearly 2%. In addition, we also conducted experiments on the imbalanced datasets: Amazon and YelpChi. The results showed that our model GDFGAT performed better than the baseline model in some metrics.

  6. f

    Sichuan telecom fraud dataset static analysis.

    • plos.figshare.com
    • figshare.com
    xls
    Updated May 30, 2025
    + more versions
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    An Tong; Bochao Chen; Zhe Wang; Jiawei Gao; Chi Kin Lam (2025). Sichuan telecom fraud dataset static analysis. [Dataset]. http://doi.org/10.1371/journal.pone.0322004.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 30, 2025
    Dataset provided by
    PLOS ONE
    Authors
    An Tong; Bochao Chen; Zhe Wang; Jiawei Gao; Chi Kin Lam
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In recent years, the number of telecom frauds has increased significantly, causing substantial losses to people’s daily lives. With technological advancements, telecom fraud methods have also become more sophisticated, making fraudsters harder to detect as they often imitate normal users and exhibit highly similar features. Traditional graph neural network (GNN) methods aggregate the features of neighboring nodes, which makes it difficult to distinguish between fraudsters and normal users when their features are highly similar. To address this issue, we proposed a spatio-temporal graph attention network (GDFGAT) with feature difference-based weight updates. We conducted comprehensive experiments on our method on a real telecom fraud dataset. Our method obtained an accuracy of 93.28%, f1 score of 92.08%, precision rate of 93.51%, recall rate of 90.97%, and AUC value of 94.53%. The results showed that our method (GDFGAT) is better than the classical method, the latest methods and the baseline model in many metrics; each metric improved by nearly 2%. In addition, we also conducted experiments on the imbalanced datasets: Amazon and YelpChi. The results showed that our model GDFGAT performed better than the baseline model in some metrics.

  7. f

    Changing patterns in deforestation avoidance by different protection types...

    • plos.figshare.com
    7z
    Updated Jun 6, 2023
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    Tomas Jusys (2023). Changing patterns in deforestation avoidance by different protection types in the Brazilian Amazon [Dataset]. http://doi.org/10.1371/journal.pone.0195900
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    7zAvailable download formats
    Dataset updated
    Jun 6, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Tomas Jusys
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Amazon Rainforest
    Description

    This study quantifies how much deforestation was avoided due to legal protection in Legal Amazon in strictly protected areas, sustainable use areas, and indigenous lands. Only regions that are protected de jure (i.e., where deforestation is avoided due to effective laws rather than remoteness) were considered, so that the potential of legal protection could be better assessed. This is a cross-sectional approach, which allows comparisons in terms of avoided deforestation among the different types of protection in the same period. This study covers three different periods. Regions protected de jure were sampled by estimating a threshold distance at which deforestation starts to diminish and retaining all pixels up to that distance, and deforestation that has been avoided due to legal protection was estimated by matching. Indigenous lands avoided the highest percentage of deforestation during the 2001–2004 and 2005–2008 periods, followed by those under strict protection and sustainable use areas, in respective order. Shifting patterns in deforestation avoidance are clearly noticeable for the 2009–2014 period when 1) strictly protected areas outperformed indigenous lands in terms of the percentage of saved forests, 2) some protected regions began to attract deforestation instead of avoiding it, and 3) sustainable use areas, on average, did not avoid deforestation.

  8. Amazon Web Services: year-on-year growth 2014-2025

    • statista.com
    Updated May 13, 2025
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    Statista (2025). Amazon Web Services: year-on-year growth 2014-2025 [Dataset]. https://www.statista.com/statistics/422273/yoy-quarterly-growth-aws-revenues/
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    Dataset updated
    May 13, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    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.

  9. Quarterly Netflix subscribers count worldwide 2013-2024

    • statista.com
    • ai-chatbox.pro
    Updated Jun 23, 2025
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    Statista (2025). Quarterly Netflix subscribers count worldwide 2013-2024 [Dataset]. https://www.statista.com/statistics/250934/quarterly-number-of-netflix-streaming-subscribers-worldwide/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    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.

  10. Global retail e-commerce sales 2022-2028

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). Global retail e-commerce sales 2022-2028 [Dataset]. https://www.statista.com/statistics/379046/worldwide-retail-e-commerce-sales/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2025
    Area covered
    Worldwide
    Description

    In 2024, global retail e-commerce sales reached an estimated ************ U.S. dollars. Projections indicate a ** percent growth in this figure over the coming years, with expectations to come close to ************** dollars by 2028. World players Among the key players on the world stage, the American marketplace giant Amazon holds the title of the largest e-commerce player globally, with a gross merchandise value of nearly *********** U.S. dollars in 2024. Amazon was also the most valuable retail brand globally, followed by mostly American competitors such as Walmart and the Home Depot. Leading e-tailing regions E-commerce is a dormant channel globally, but nowhere has it been as successful as in Asia. In 2024, the e-commerce revenue in that continent alone was measured at nearly ************ U.S. dollars, outperforming the Americas and Europe. That year, the up-and-coming e-commerce markets also centered around Asia. The Philippines and India stood out as the swiftest-growing e-commerce markets based on online sales, anticipating a growth rate surpassing ** percent.

  11. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Statista (2025). Global net revenue of Amazon 2014-2024, by product group [Dataset]. https://www.statista.com/statistics/672747/amazons-consolidated-net-revenue-by-segment/
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Global net revenue of Amazon 2014-2024, by product group

Explore at:
19 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Feb 24, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

In 2024, Amazon's net revenue from subscription services segment amounted to 44.37 billion U.S. dollars. Subscription services include Amazon Prime, for which Amazon reported 200 million paying members worldwide at the end of 2020. The AWS category generated 107.56 billion U.S. dollars in annual sales. During the most recently reported fiscal year, the company’s net revenue amounted to 638 billion U.S. dollars. Amazon revenue segments Amazon is one of the biggest online companies worldwide. In 2019, the company’s revenue increased by 21 percent, compared to Google’s revenue growth during the same fiscal period, which was just 18 percent. The majority of Amazon’s net sales are generated through its North American business segment, which accounted for 236.3 billion U.S. dollars in 2020. The United States are the company’s leading market, followed by Germany and the United Kingdom. Business segment: Amazon Web Services Amazon Web Services, commonly referred to as AWS, is one of the strongest-growing business segments of Amazon. AWS is a cloud computing service that provides individuals, companies and governments with a wide range of computing, networking, storage, database, analytics and application services, among many others. As of the third quarter of 2020, AWS accounted for approximately 32 percent of the global cloud infrastructure services vendor market.

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