The Ministry of Transportation and Communications Tourism Bureau collects spatial tourism information released by various government agencies, including information on tourist attractions, activities, dining and lodging, tourist service stations, hiking trails, bike paths, and other data, providing comprehensive tourism GIS basic data for operators to add value. The XML field descriptions for each dataset, tourism data standard V1.0 data, please refer to https://media.taiwan.net.tw/Upload/TourismInformationStandardFormatV1.0.pdf; tourism data standard V2.0 data, please refer to https://media.taiwan.net.tw/Upload/TourismDataStandardV2.0.pdf.

[Metadata] Locations of the Visitor Plant Inventory (VPI) in the State of Hawaii (updated December, 2021). Source: Hawaii Tourism Authority, September 2022. This inventory includes apartment hotels, bed and breakfasts (B&Bs), condominium hotels, hostels, hotels, individual vacation units, timeshares, and other types of visitor accommodations.

Comprehensive dataset of 91,745 Hotels in United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The dataset contains locations and attributes of Hotels, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. A database provided by the DC Taxi Commission (DCTC) and research at various commercial websites identified Hotels and DC GIS staff geo-processed the data.

We will create a customized hotels dataset tailored to your specific requirements. Data points may include hotel names, location details, pricing information, amenity lists, guest ratings, occupancy rates, and other relevant metrics.

Utilize our hotels datasets for a variety of applications to boost strategic planning and market analysis. Analyzing these datasets can help organizations understand guest preferences and market trends within the hospitality industry, allowing for more precise operational adjustments and marketing strategies. You can choose to access the complete dataset or a customized subset based on your business needs.

Popular use cases include: optimizing booking strategies, enhancing guest experience, and competitive benchmarking.

In May 2024, the region with the highest hotel occupancy rate worldwide was Europe, at 73 percent, showing a one percent increase over the previous year. Meanwhile, the lower occupancy rates across the board in 2020 and 2021 were due to the impact of the coronavirus (COVID-19) pandemic on the hotel industry.

Comprehensive dataset of 5 Hotel rooms in United States as of August, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Data includes occupancy rates, average daily rates, and revenue per available room.

This dataset contains examples of customer reviews of three hotels.The study is in Excel format and consists of three pages. Each page contains forty comments about the hotel. There are 120 sample hotel reviews in total.

Metrics that can be unearthed will be ones contained in the email booking invoice such as Hotel name, type of room, dates, check in and check out times, price paid, duration of stay. We can go back to 5 years of history.

We also have cancellation emails.

Any hotel vendor can be requested too. We will conduct a search in our database to see if it justifies a parser build to extract the data.

Please contact michelle@measurable.ai for a demo or more data samples.

Taiwan General Hotel: Number of Hotel data was reported at 3,885.000 Unit in 2017. This records an increase from the previous number of 3,688.000 Unit for 2016. Taiwan General Hotel: Number of Hotel data is updated yearly, averaging 3,239.000 Unit from Dec 2003 (Median) to 2017, with 15 observations. The data reached an all-time high of 3,885.000 Unit in 2017 and a record low of 3,151.000 Unit in 2010. Taiwan General Hotel: Number of Hotel data remains active status in CEIC and is reported by Tourism Bureau, Ministry of Transportation and Communications. The data is categorized under Global Database’s Taiwan – Table TW.Q020: Hotel Statistics: General Hotel: Number of Hotels and Rooms (Annual).

The OTA, booking websites have a ton of information like pricing, promotions, occupancy reviews, etc about hotels. Our data as a service offering helps our customers get this data through web scraping. The data is refreshed every day and delivered to our customers via Amazon S3, The most common use cases are competitive intelligence and marketing spend optimization.

No. of Hotel Room: Tourist Center: Culiacan data was reported at 12,033.000 Unit in 31 Mar 2024. This stayed constant from the previous number of 12,033.000 Unit for 24 Mar 2024. No. of Hotel Room: Tourist Center: Culiacan data is updated weekly, averaging 16,709.000 Unit from Jan 2006 (Median) to 31 Mar 2024, with 952 observations. The data reached an all-time high of 19,915.000 Unit in 28 Nov 2021 and a record low of 12,033.000 Unit in 31 Mar 2024. No. of Hotel Room: Tourist Center: Culiacan data remains active status in CEIC and is reported by Secretary of Tourism. The data is categorized under Global Database’s Mexico – Table MX.Q019: Number of Hotel Room: by Tourist Center. [COVID-19-IMPACT]

The Agoda Hotel Listings Dataset provides a structured and detailed view of accommodations worldwide, offering essential data for travel industry professionals, market analysts, and businesses. This dataset includes key details such as hotel names, locations, review scores, pricing, availability, room configurations, amenities, guest reviews, property highlights, and property surroundings.

With this dataset, users can:

Analyze market trends to understand booking behaviors, pricing dynamics, and seasonal demand.
Enhance travel recommendations by identifying top-rated hotels based on reviews, location, and amenities.
Optimize pricing and revenue strategies by benchmarking property performance and availability patterns.
Assess guest satisfaction through sentiment analysis of ratings and reviews.
Refine location-based insights by analyzing property surroundings and nearby attractions.

Designed for hospitality businesses, travel platforms, AI-powered recommendation engines, and pricing strategists, this dataset enables data-driven decision-making to improve customer experience and business performance.

Use Cases

Agoda Hotel Listings in Thailand
Gain insights into Thailand’s hospitality market, from luxury resorts in Phuket to boutique hotels in Bangkok. Analyze review scores, availability trends, and traveler preferences to refine booking strategies.
Agoda Hotel Listings in Japan
Explore hotel data across Japan’s major cities and rural retreats, ideal for travel planners targeting visitors to Tokyo, Kyoto, and Osaka. This dataset includes review scores, pricing, and property highlights.
Agoda Hotel Listings with Review Scores Greater Than 9
A curated selection of high-rated hotels worldwide, ideal for luxury travel planners and market researchers focused on premium accommodations that consistently exceed guest expectations.
Agoda Hotel Listings in the United States with More Than 1000 Reviews
Analyze well-established and highly reviewed hotels across the U.S., ensuring reliable guest feedback for market insights and customer satisfaction benchmarking.

This dataset serves as an indispensable resource for travel analysts, hospitality businesses, and data-driven decision-makers, providing the intelligence needed to stay competitive in the ever-evolving travel industry.

The Hotel Area KPIs dataset provides comprehensive insights into hotel performance metrics across global markets.

Sourced directly from hotel reservation systems, this dataset offers a real-time view of key performance indicators such as occupancy rates, average daily rates (ADR), revenue per available room (RevPAR), and booking patterns.

With weekly updates and both historical and forward-looking data, it enables hoteliers, investors, and analysts to track market trends, benchmark performance, and make data-driven decisions.

This dataset is invaluable for understanding seasonal variations, forecasting demand, and optimizing pricing strategies in the dynamic hospitality industry.

Local Hotel Occupancy Tax (HOT) data has been compiled by municipalities complying with Tax Code Section 351.009 since 2018. In January 2021, counties began reporting their HOT data in accordance with Tax Code Section 352.009. If local HOT data related to a specific municipality or county is not available in this dataset, it may be because that entity does not levy such a tax or that the local government failed to submit their information to the Comptroller's office within the specified reporting period. The data reported through the Comptroller's Local HOT Submission Form and available in this dataset is self-reported by submitting municipalities, counties, or third parties on their behalf and has not been independently verified by the Texas Comptroller of Public Accounts. Specific questions or concerns regarding a local government's HOT rate, revenue, allocations and/or submitted webpage links should be directed to that entity. General questions regarding this spreadsheet, Tax Code Sections 351.009 or 352.009 may be directed to the Comptroller’s Transparency Team, either by email (transparency@cpa.texas.gov) or by phone (844-519-5676).

This dataset includes quantitative and categorical features from online reviews from 21 hotels located in Las Vegas Strip, extracted from TripAdvisor (http://www.tripadvisor.com). All the 504 reviews were collected between January and August of 2016. The dataset contains 504 records and 20 tuned features (as of “status = included”, from Table 1 of the article mentioned below), 24 per hotel (two per each month, randomly selected), regarding the year of 2015.

Dataset

This dataset was created by Amine Elyazidi

Released under CC0: Public Domain

Contents

The hotel registry of Kinmen County describes.....

Hotels and Motels dataset current as of 2006. casino hotel data set.