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In 2021, Apple's advertising revenue in the United States grew by **** percent. This is the highest value in the period of 2020 to 2024 presented in the data set. The source projected that after 2021, the growth will gradually slow down but will remain in a double-digit range.

Dataset

This dataset was created by Shreeya Agrawal

Contents

Published in September 2020, Genshin Impact has quickly shot up the rank among the top-grossing mobile games worldwide. In May 2025, the mobile app generated approximately 27.7 million U.S. dollars in in-app purchases. The open-world action RPG title uses a gacha game monetization system and is available for several platforms and claims the title of the fastest gaming app to reach 5 billion U.S. dollars in global player spending. Anime-style open world online games Inspired by Genshin’s success story, many other app publishers have tried to recapture the game’s success. Chinese app developers, in particular, have been homing in on the anime-style open world fantasy genre, though none of these releases have managed to reach Genshin’s level of impact. Tower of Fantasy, developed by Hotta Studio, was published in December 2021, making it one of the earlier entries of the genre. Not putting all its eggs in one basket, Genshin publisher miHoYo also released another game with similar mechanics to GI, the space fantasy RPG Honkai: Star Rail. While not reaching Genshin’s runaway financial success, Honkai: Star Rail has managed to prove itself a financial success in its own right. In May 2024, Kuro Games released the highly anticipated Wuthering Waves. Wuthering Waves’ mobile app accumulated over 20 million U.S. dollars in IAP revenues within 10 days of release, showing that gaming audiences are still hungry for open world online games. The success of online anime RPGs is not guaranteed Despite the popularity of the genre, games in this segment are not automatically poised for success. Japanese publisher Bandai Namco also created an anime MMORPG, Blue Protocol. Originally planned for a worldwide multi-platform release with Amazon as a global publisher in 2023, the game received a Japan-only launch in the summer of 2023, the Korean launch was moved to 2024 and then infinitely paused. Despite a strong launch, the game has fizzled out and Japanese gamers have criticized Blue Protocol for the lack of engaging features, bugs, and lack of serious content updates, highlighting Bandai’s inability to tap into the genre and keep up with online gaming trends despite its status as an AAA-level video gaming company.

In today's digital landscape, data transparency and compliance are paramount. Organizations across industries are striving to maintain trust and adhere to regulations governing data privacy and security. To support these efforts, we present our comprehensive Ads.txt and App-Ads.txt dataset.

Key Benefits of Our Dataset:

• Coverage: Our dataset offers a comprehensive view of the Ads.txt and App-Ads.txt files, providing valuable information about publishers, advertisers, and the relationships between them. You gain a holistic understanding of the digital advertising ecosystem.
• Multiple Data Formats: We understand that flexibility is essential. Our dataset is available in multiple formats, including .CSV, .JSON, and more. Choose the format that best suits your data processing needs.
• Global Scope: Whether your business operates in a single country or spans multiple continents, our dataset is tailored to meet your needs. It provides data from various countries, allowing you to analyze regional trends and compliance.
  • Top-Quality Data: Quality matters. Our dataset is meticulously curated and continuously updated to deliver the most accurate and reliable information. Trust in the integrity of your data for critical decision-making.
  • Seamless Integration: We've designed our dataset to seamlessly integrate with your existing systems and workflows. No disruptions—just enhanced compliance and efficiency.

The Power of Ads.txt & App-Ads.txt: Ads.txt (Authorized Digital Sellers) and App-Ads.txt (Authorized Sellers for Apps) are industry standards developed by the Interactive Advertising Bureau (IAB) to increase transparency and combat ad fraud. These files specify which companies are authorized to sell digital advertising inventory on a publisher's website or app. Understanding and maintaining these files is essential for data compliance and the prevention of unauthorized ad sales.

How Can You Benefit? - Data Compliance: Ensure that your organization adheres to industry standards and regulations by monitoring Ads.txt and App-Ads.txt files effectively. - Ad Fraud Prevention: Identify unauthorized sellers and take action to prevent ad fraud, ultimately protecting your revenue and brand reputation. - Strategic Insights: Leverage the data in these files to gain insights into your competitors, partners, and the broader digital advertising landscape. - Enhanced Decision-Making: Make data-driven decisions with confidence, armed with accurate and up-to-date information about your advertising partners. - Global Reach: If your operations span the globe, our dataset provides insights into the Ads.txt and App-Ads.txt files of publishers worldwide.

Multiple Data Formats for Your Convenience: - CSV (Comma-Separated Values): A widely used format for easy data manipulation and analysis in spreadsheets and databases. - JSON (JavaScript Object Notation): Ideal for structured data and compatibility with web applications and APIs. - Other Formats: We understand that different organizations have different preferences and requirements. Please inquire about additional format options tailored to your needs.

Data That You Can Trust:

We take data quality seriously. Our team of experts curates and updates the dataset regularly to ensure that you receive the most accurate and reliable information available. Your confidence in the data is our top priority.

Seamless Integration:

Integrate our Ads.txt and App-Ads.txt dataset effortlessly into your existing systems and processes. Our goal is to enhance your compliance efforts without causing disruptions to your workflow.

In Conclusion:

Transparency and compliance are non-negotiable in today's data-driven world. Our Ads.txt and App-Ads.txt dataset empowers you with the knowledge and tools to navigate the complexities of the digital advertising ecosystem while ensuring data compliance and integrity. Whether you're a Data Protection Officer, a data compliance professional, or a business leader, our dataset is your trusted resource for maintaining data transparency and safeguarding your organization's reputation and revenue.

Get Started Today:

Don't miss out on the opportunity to unlock the power of data transparency and compliance. Contact us today to learn more about our Ads.txt and App-Ads.txt dataset, available in multiple formats and tailored to your specific needs. Join the ranks of organizations worldwide that trust our dataset for a compliant and transparent future.

Amazon Sales Report

Overview:

This dataset provides detailed sales data from Amazon, offering a comprehensive look at various product categories and their performance over time. It includes information on sales figures, order details, product categories, and customer demographics.

Features:

1. Order ID

Description: A unique identifier for each order placed on Amazon. This field helps to track individual orders and link related records.

2. Dates

Description: The date when the order was placed. This field is crucial for analyzing sales trends over time and identifying seasonal patterns.

3. Status

Description: The current status of the order (e.g., Shipped, Delivered, Pending). This field provides insight into the order fulfillment process and helps monitor order processing efficiency.

4. Fulfillment

Description: Indicates the method used to fulfill the order (e.g., Fulfilled by Amazon, Fulfilled by Seller). This feature helps in analyzing the performance of different fulfillment methods and their impact on customer satisfaction.

5. Sales Channel

Description: The channel through which the sale was made (e.g., Amazon Website, Mobile App). This field is useful for evaluating the effectiveness of different sales channels and understanding customer preferences.

6. Category

Description: The product category to which the purchased item belongs (e.g., Electronics, Clothing, Home Goods). This feature aids in analyzing sales performance across various product categories.

7. Ship Service Level

Description: The shipping service level selected for the order (e.g., Standard Shipping, Two-Day Shipping). This field helps to assess the impact of shipping options on delivery times and customer satisfaction.

8. Size

Description: The size of the product ordered (e.g., Small, Medium, Large). This feature is relevant for analyzing sales performance based on product size and understanding inventory requirements.

9. Carrier Status

Description: The status of the shipment with the carrier (e.g., In Transit, Delivered, Returned). This field provides insights into the shipping process and helps in monitoring delivery performance and handling returns.

Use Cases:

Sales Analysis:

Examine trends in sales over time, identify peak periods, and analyze performance by product category.

Customer Insights:

Explore customer demographics to understand purchasing behavior and preferences.

Inventory Management:

Assess which products are performing well and which are not, aiding in inventory and supply chain management.

Marketing Strategies:

Develop targeted marketing campaigns based on sales trends and customer profiles.

Data Source:

This dataset is a simulated collection of Amazon sales data and is intended for educational and analytical purposes.

Acknowledgments:

This dataset was created to facilitate data analysis and machine learning projects. It is ideal for practicing data manipulation, statistical analysis, and predictive modeling.

Selling virtual goods and currencies to consumers has grown into a major revenue model in digital games and online services. The Virtual Goods and Currencies Data Set is a freely available data set that describes the prices and other attributes of 11,289 virtual goods and currencies. The data set is drawn from 59 game titles on mobile, social media, and PC platforms.

The DC Office of the Chief Financial Officer (OCFO), Office of Tax and Revenue (OTR), Real Property Tax Administration (RPTA) values all real property in the District of Columbia. This public interactive Real Property Assessment map application accompanies the OCFO MyTax DC and OTR websites. Use this mapping application to search for and view all real property, assessment valuation data, assessment neighborhood areas and sub-areas, detailed assessment information, and many real property valuation reports by various political and administrative areas. View by other administrative areas such as DC Wards, ANCs, DC Squares, and by specific real property characteristics such as property type and/or sale date. If you have questions, comments, or suggestions regarding the Real Property Assessment Map, contact the Real Property Assessment Division GIS Program at (202) 442-6484 or maps.title@dc.gov.

Our travel datasets provide extensive, structured data covering various aspects of the global travel and hospitality industry. These datasets are ideal for businesses, analysts, and developers looking to gain insights into hotel pricing, short-term rentals, restaurant listings, and travel trends. Whether you're optimizing pricing strategies, analyzing market trends, or enhancing travel-related applications, our datasets offer the depth and accuracy you need.

Key Travel Datasets Available:

  Hotel & Rental Listings: Access detailed data on hotel properties, short-term rentals, and vacation stays from platforms like 
    Airbnb, Booking.com, and other OTAs. This includes property details, pricing, availability, guest reviews, and amenities.

  Real-Time & Historical Pricing Data: Track hotel room pricing, rental occupancy rates, and pricing trends 
    to optimize revenue management and competitive analysis.

  Restaurant Listings & Reviews: Explore restaurant data from Tripadvisor, OpenTable, Zomato, Deliveroo, and Talabat, 
    including restaurant details, customer ratings, menus, and delivery availability.

  Market & Trend Analysis: Use structured datasets to analyze travel demand, seasonal trends, and consumer preferences 
    across different regions.

  Geo-Targeted Data: Get location-specific insights with city, state, and country-level segmentation, 
    allowing for precise market research and localized business strategies.



Use Cases for Travel Datasets:

  Dynamic Pricing & Revenue Optimization: Adjust pricing strategies based on real-time market trends and competitor analysis.
  Market Research & Competitive Intelligence: Identify emerging travel trends, monitor competitor performance, and assess market demand.
  Travel & Hospitality App Development: Enhance travel platforms with accurate, up-to-date data on hotels, restaurants, and rental properties.
  Investment & Financial Analysis: Evaluate travel industry performance for investment decisions and economic forecasting.



  Our travel datasets are available in multiple formats (JSON, CSV, Excel) and can be delivered via 
  API, cloud storage (AWS, Google Cloud, Azure), or direct download. 
  Stay ahead in the travel industry with high-quality, structured data that powers smarter decisions.

The CDTFA Mobile app will enable you to find a sales and use tax rate, locate and contact our field offices, and conveniently access our website and online services.

FEATURES

• California Sales and Use Tax Rates: Find a tax rate by address, city, or your current location • CDTFA Field Offices: Get an office's address and other details, and with the tap of a button call an office or open its location in the Maps application to get driving directions • Website: View our website right within the app • Online Services: Access our online services directly with the tap of a button • And more features will be coming soon!

Global Backend Database Software is segmented by Application (Enterprise apps, Web backends, Analytics, IoT, Mobile apps), Type (Relational, NoSQL, Cloud-native, In-memory, Graph) and Geography(North America, LATAM, West Europe, Central & Eastern Europe, Northern Europe, Southern Europe, East Asia, Southeast Asia, South Asia, Central Asia, Oceania, MEA)

A Dashboard to explore the City's Expenditures against Revenue. &nbspUpdate Schedule: Once per month.

Apple is one of the most influential and recognisable brands in the world, responsible for the rise of the smartphone with the iPhone. Valued at over $2 trillion in 2021, it is also the most valuable...

Find a Sales and Use Tax RateFind a CDTFA office and get directions

Here are a few use cases for this project:

1. Retail Inventory Management: The "Sale Detection" model can be used in stores to automate tracking of ongoing sales and discounts in real time, enabling store managers to monitor inventory levels and re-stock items more efficiently.

2. Shopping Assistant Apps: The model can be integrated into shopping apps that help consumers find the best deals and discounts on products by scanning shelves or store displays and detecting sale signs or price reductions.

3. Digital Marketing & Advertising Analysis: The "Sale Detection" model can be used by marketing professionals to analyze the effectiveness of various sales promotions based on customer responses, helping them optimize future marketing campaigns.

4. Dynamic Pricing and Revenue Optimization: E-commerce platforms and online retailers can use the "Sale Detection" model to analyze competitor prices and promotions, allowing them to adjust their own prices and offers dynamically to remain competitive.

5. Customer Behavior Analysis: The model can be used to analyze in-store customer behavior and engagement, such as how much time customers spend in specific sale areas, which sales tactics attract more attention, and what types of sales promotions generate the most customer interactions.

The Canadian contribution and data set prepared as part of the Global Media and Internet Concentration (GMIC) project offers an independent academic, empirical and data-driven analysis of a deceptively simple yet profoundly important question: have telecom, media and internet markets become more concentrated over time, or less? Media Ownership and Concentration is presented from more than a dozen sectors of the telecom-media-internet industries, including film, music and book industries. Note: The Master GMICP Workbook was revised to remove instances where App Store and advertising revenue for Advertising-based Video-on-Demand (AVOD) services delivered over the Internet had been double counted in the original data set released through Dataverse. The text of the report was also revised to reflect these corrections.

Ecommerce marketplace app Shopee started life out as a customer-to-customer marketplace, in the same vein as eBay, but over the past few years has remodelled itself as a b2c marketplace. That switch...

Contains revenue sources to support York Region's operating budget.

These are the Airbnb statistics on gross revenue by country.