Version 11.1 Release Date: August 22, 2022
The Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. These data and their derivatives are the only international boundary lines approved for U.S. Government use. They reflect U.S. Government policy, and not necessarily de facto limits of control. This dataset is a National Geospatial Data Asset.
Sources for these data include treaties, relevant maps, and data from boundary commissions and national mapping agencies. Where available, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery of the data involves analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground.
The dataset uses the following attributes: Attribute Name Explanation Country Code Country-level codes are from the Geopolitical Entities, Names, and Codes Standard (GENC). The Q2 code denotes a line representing a boundary associated with an area not in GENC. Country Names Names approved by the U.S. Board on Geographic Names (BGN). Names for lines associated with a Q2 code are descriptive and are not necessarily BGN-approved. Label Required text label for the line segment where scale permits Rank/Status Rank 1: International Boundary Rank 2: Other Line of International Separation Rank 3: Special Line Notes Explanation of any applicable special circumstances Cartographic Usage Depiction of the LSIB requires a visual differentiation between the three categories of boundaries: International Boundaries (Rank 1), Other Lines of International Separation (Rank 2), and Special Lines (Rank 3). Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary. Additional cartographic information can be found in Guidance Bulletins (https://hiu.state.gov/data/cartographic_guidance_bulletins/) published by the Office of the Geographer and Global Issues. Please direct inquiries to internationalboundaries@state.gov.
The lines in the LSIB dataset are the product of decades of collaboration between geographers at the Department of State and the National Geospatial-Intelligence Agency with contributions from the Central Intelligence Agency and the UK Defence Geographic Centre. Attribution is welcome: U.S. Department of State, Office of the Geographer and Global Issues.
This version of the LSIB contains changes and accuracy refinements for the following line segments. These changes reflect improvements in spatial accuracy derived from newly available source materials, an ongoing review process, or the publication of new treaties or agreements. Changes to lines include: • Akrotiri (UK) / Cyprus • Albania / Montenegro • Albania / Greece • Albania / North Macedonia • Armenia / Turkey • Austria / Czechia • Austria / Slovakia • Austria / Hungary • Austria / Slovenia • Austria / Germany • Austria / Italy • Austria / Switzerland • Azerbaijan / Turkey • Azerbaijan / Iran • Belarus / Latvia • Belarus / Russia • Belarus / Ukraine • Belarus / Poland • Bhutan / India • Bhutan / China • Bulgaria / Turkey • Bulgaria / Romania • Bulgaria / Serbia • Bulgaria / Romania • China / Tajikistan • China / India • Croatia / Slovenia • Croatia / Hungary • Croatia / Serbia • Croatia / Montenegro • Czechia / Slovakia • Czechia / Poland • Czechia / Germany • Finland / Russia • Finland / Norway • Finland / Sweden • France / Italy • Georgia / Turkey • Germany / Poland • Germany / Switzerland • Greece / North Macedonia • Guyana / Suriname • Hungary / Slovenia • Hungary / Serbia • Hungary / Romania • Hungary / Ukraine • Iran / Turkey • Iraq / Turkey • Italy / Slovenia • Italy / Switzerland • Italy / Vatican City • Italy / San Marino • Kazakhstan / Russia • Kazakhstan / Uzbekistan • Kosovo / north Macedonia • Kosovo / Serbia • Kyrgyzstan / Tajikistan • Kyrgyzstan / Uzbekistan • Latvia / Russia • Latvia / Lithuania • Lithuania / Poland • Lithuania / Russia • Moldova / Ukraine • Moldova / Romania • Norway / Russia • Norway / Sweden • Poland / Russia • Poland / Ukraine • Poland / Slovakia • Romania / Ukraine • Romania / Serbia • Russia / Ukraine • Syria / Turkey • Tajikistan / Uzbekistan
This release also contains topology fixes, land boundary terminus refinements, and tripoint adjustments.
While U.S. Government works prepared by employees of the U.S. Government as part of their official duties are not subject to Federal copyright protection (see 17 U.S.C. § 105), copyrighted material incorporated in U.S. Government works retains its copyright protection. The works on or made available through download from the U.S. Department of State’s website may not be used in any manner that infringes any intellectual property rights or other proprietary rights held by any third party. Use of any copyrighted material beyond what is allowed by fair use or other exemptions may require appropriate permission from the relevant rightsholder. With respect to works on or made available through download from the U.S. Department of State’s website, neither the U.S. Government nor any of its agencies, employees, agents, or contractors make any representations or warranties—express, implied, or statutory—as to the validity, accuracy, completeness, or fitness for a particular purpose; nor represent that use of such works would not infringe privately owned rights; nor assume any liability resulting from use of such works; and shall in no way be liable for any costs, expenses, claims, or demands arising out of use of such works.
List of the data tables as part of the Immigration System Statistics Home Office release. Summary and detailed data tables covering the immigration system, including out-of-country and in-country visas, asylum, detention, and returns.
If you have any feedback, please email MigrationStatsEnquiries@homeoffice.gov.uk.
The Microsoft Excel .xlsx files may not be suitable for users of assistive technology.
If you use assistive technology (such as a screen reader) and need a version of these documents in a more accessible format, please email MigrationStatsEnquiries@homeoffice.gov.uk
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Immigration system statistics, year ending March 2025
Immigration system statistics quarterly release
Immigration system statistics user guide
Publishing detailed data tables in migration statistics
Policy and legislative changes affecting migration to the UK: timeline
Immigration statistics data archives
https://assets.publishing.service.gov.uk/media/68258d71aa3556876875ec80/passenger-arrivals-summary-mar-2025-tables.xlsx">Passenger arrivals summary tables, year ending March 2025 (MS Excel Spreadsheet, 66.5 KB)
‘Passengers refused entry at the border summary tables’ and ‘Passengers refused entry at the border detailed datasets’ have been discontinued. The latest published versions of these tables are from February 2025 and are available in the ‘Passenger refusals – release discontinued’ section. A similar data series, ‘Refused entry at port and subsequently departed’, is available within the Returns detailed and summary tables.
https://assets.publishing.service.gov.uk/media/681e406753add7d476d8187f/electronic-travel-authorisation-datasets-mar-2025.xlsx">Electronic travel authorisation detailed datasets, year ending March 2025 (MS Excel Spreadsheet, 56.7 KB)
ETA_D01: Applications for electronic travel authorisations, by nationality
ETA_D02: Outcomes of applications for electronic travel authorisations, by nationality
https://assets.publishing.service.gov.uk/media/68247953b296b83ad5262ed7/visas-summary-mar-2025-tables.xlsx">Entry clearance visas summary tables, year ending March 2025 (MS Excel Spreadsheet, 113 KB)
https://assets.publishing.service.gov.uk/media/682c4241010c5c28d1c7e820/entry-clearance-visa-outcomes-datasets-mar-2025.xlsx">Entry clearance visa applications and outcomes detailed datasets, year ending March 2025 (MS Excel Spreadsheet, 29.1 MB)
Vis_D01: Entry clearance visa applications, by nationality and visa type
Vis_D02: Outcomes of entry clearance visa applications, by nationality, visa type, and outcome
Additional dat
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All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name
The data were produced by WorldPop at the University of Southampton. These data include gridded population estimates, at approximately 100m resolution, for 40 countries in Latin America and the Caribbean (Appendix A). These results were created using official population estimates at the finest-available resolution provided by National Statistic Offices (NSOs) throughout the region, and built-up area, height and volume covariates produced from World Settlement Footprint 3D (WSF3D) datasets1. We acknowledge the contribution of WorldPop’s partners, notably the United Nations Population Fund (UNFPA) Latin America and Caribbean Regional Office in supporting the collection of population and administrative boundary data, and to the German Aerospace Center (DLR) for preparing and providing built settlement data from the WSF3D framework. Modelling work and geospatial data processing was carried out by McKeen T., Bondarenko M., Kerr D. and Sorichetta A. Esch T., Marconcini M., Zeidler J. and Palacios-Lopez D. prepared and provided the WSF3D datasets. Juran S. and Valle C. aided with population and administrative boundary data collection. Oversight was provided by Andrew J. Tatem fourth and final part.
This information covers fires, false alarms and other incidents attended by firecrews, and the statistics include the numbers of incidents, fires, fatalities and casualties as well as information on response times to fires. The Home Office also collect information on the workforce, fire prevention work, health and safety and firefighter pensions. All data tables on fire statistics are below.
The Home Office has responsibility for fire services in England. The vast majority of data tables produced by the Home Office are for England but some (0101, 0103, 0201, 0501, 1401) tables are for Great Britain split by nation. In the past the Department for Communities and Local Government (who previously had responsibility for fire services in England) produced data tables for Great Britain and at times the UK. Similar information for devolved administrations are available at https://www.firescotland.gov.uk/about-us/fire-and-rescue-statistics.aspx" class="govuk-link">Scotland: Fire and Rescue Statistics, https://statswales.gov.wales/Catalogue/Community-Safety-and-Social-Inclusion/Community-Safety" class="govuk-link">Wales: Community safety and http://www.nifrs.org/" class="govuk-link">Northern Ireland: Fire and Rescue Statistics.
If you use assistive technology (eg a screen reader) and need a version of any of these documents in a more accessible format, please email alternativeformats@homeoffice.gsi.gov.uk. Please tell us what format you need. It will help us if you say what assistive technology you use.
Fire statistics guidance
Fire statistics incident level datasets
FIRE0101: Incidents attended by fire and rescue services by nation and population (MS Excel Spreadsheet, 44.5KB) Previous FIRE0101 tables
FIRE0102: Incidents attended by fire and rescue services in England, by incident type and fire and rescue authority (MS Excel Spreadsheet, 1.34MB) Previous FIRE0102 tables
FIRE0103: Fires attended by fire and rescue services by nation and population (MS Excel Spreadsheet, 66.6KB) Previous FIRE0103 tables
FIRE0104: Fire false alarms by reason for false alarm, England (MS Excel Spreadsheet, 203KB) Previous FIRE0104 tables
FIRE0201: Dwelling fires attended by fire and rescue services by motive, population and nation (MS Excel Spreadsheet, 60.7KB) <a href="https://www.gov.uk/government/statistical-data-sets/fire0201-previous-da
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This dataset provides values for GOLD RESERVES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
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The purpose of this initiative is to build an integrated dataset on Intensive Care Units (ICUs) and their availability by country and region (at the highest regional granularity provided by the sources), using a data model standardized across countries.
Currently, ICU data is stored in different country-specific sources, with a wide range of access points (national websites, APIs, excel or csv files, etc.)
Given current COVID-19 crisis, we believe that this information should be provided with the following: * common standardized structure * single point of access * open to the public
We hope that these datasets will further benefit researchers and help us in the fight against COVID-19.
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Chad TD: GDP: USD: Gross National Income per Capita: Atlas Method data was reported at 670.000 USD in 2023. This records an increase from the previous number of 660.000 USD for 2022. Chad TD: GDP: USD: Gross National Income per Capita: Atlas Method data is updated yearly, averaging 220.000 USD from Dec 1962 (Median) to 2023, with 62 observations. The data reached an all-time high of 940.000 USD in 2014 and a record low of 110.000 USD in 1964. Chad TD: GDP: USD: Gross National Income per Capita: Atlas Method data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank.WDI: Gross Domestic Product: Nominal. GNI per capita (formerly GNP per capita) is the gross national income, converted to U.S. dollars using the World Bank Atlas method, divided by the midyear population. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. GNI, calculated in national currency, is usually converted to U.S. dollars at official exchange rates for comparisons across economies, although an alternative rate is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate actually applied in international transactions. To smooth fluctuations in prices and exchange rates, a special Atlas method of conversion is used by the World Bank. This applies a conversion factor that averages the exchange rate for a given year and the two preceding years, adjusted for differences in rates of inflation between the country, and through 2000, the G-5 countries (France, Germany, Japan, the United Kingdom, and the United States). From 2001, these countries include the Euro area, Japan, the United Kingdom, and the United States.;World Bank national accounts data, and OECD National Accounts data files.;Weighted average;
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This dataset provides values for PERSONAL SAVINGS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
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Some say climate change is the biggest threat of our age while others say it’s a myth based on dodgy science. We are turning some of the data over to you so you can form your own view.
Even more than with other data sets that Kaggle has featured, there’s a huge amount of data cleaning and preparation that goes into putting together a long-time study of climate trends. Early data was collected by technicians using mercury thermometers, where any variation in the visit time impacted measurements. In the 1940s, the construction of airports caused many weather stations to be moved. In the 1980s, there was a move to electronic thermometers that are said to have a cooling bias.
Given this complexity, there are a range of organizations that collate climate trends data. The three most cited land and ocean temperature data sets are NOAA’s MLOST, NASA’s GISTEMP and the UK’s HadCrut.
We have repackaged the data from a newer compilation put together by the Berkeley Earth, which is affiliated with Lawrence Berkeley National Laboratory. The Berkeley Earth Surface Temperature Study combines 1.6 billion temperature reports from 16 pre-existing archives. It is nicely packaged and allows for slicing into interesting subsets (for example by country). They publish the source data and the code for the transformations they applied. They also use methods that allow weather observations from shorter time series to be included, meaning fewer observations need to be thrown away.
In this dataset, we have include several files:
Global Land and Ocean-and-Land Temperatures (GlobalTemperatures.csv):
Other files include:
The raw data comes from the Berkeley Earth data page.
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This dataset provides values for INTEREST RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
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Analysis of ‘Turnover Team Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/helddata/turnover-team-data on 13 February 2022.
--- Dataset description provided by original source is as follows ---
Example data set for making some analyses with HR data Data set is licensed by Kogan Page Ltd. Only for educational purposes, as it's an example data set Data is cleaned.
The data set has been uploaded mainly to analyse team-level turnover by country and predicting team turnover
1 Team identifier (unique team number). 2 Team size (number of people in the team). 3 Team turnover 2014 (separation rate between 0 and 1). 4 Country (1 = UK; 2 = United States; 3 = CANADA; 4 = SPAIN). 5 SURVEY: ENGAGEMENT items COMBO (composite engagement percentage across the team). 6 SURVEY: TeamLeader Rating (composite team leader percentage across the team). 7 SURVEY: CSR rating (composite corporate social responsibility percentage across the team). 8 SURVEY: Drive for Performance (composite percentage team score on perceived ‘Drive for performance’ percentage). 9 SURVEY: Performance, Development and Reward (composite percentage team score on perceived fairness of performance, development and reward across the team). 10 SURVEY: Work–Life Balance (composite percentage team score on perceived work–life balance across the team). 11 UK dummy variable (0 = not UK; 1 = UK). 12 USA dummy variable (0 = not United States; 1 = United States). 13 Canada dummy variable (0 = not Canada; 1 = Canada). 14 Spain dummy variable (0 = not Spain; 1 = Spain).
--- Original source retains full ownership of the source dataset ---
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This dataset provides values for INFLATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
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Success.ai offers a cutting-edge solution for businesses and organizations seeking Company Financial Data on private and public companies. Our comprehensive database is meticulously crafted to provide verified profiles, including contact details for financial decision-makers such as CFOs, financial analysts, corporate treasurers, and other key stakeholders. This robust dataset is continuously updated and validated using AI technology to ensure accuracy and relevance, empowering businesses to make informed decisions and optimize their financial strategies.
Key Features of Success.ai's Company Financial Data:
Global Coverage: Access data from over 70 million businesses worldwide, including public and private companies across all major industries and regions. Our datasets span 250+ countries, offering extensive reach for your financial analysis and market research.
Detailed Financial Profiles: Gain insights into company financials, including revenue, profit margins, funding rounds, and operational costs. Profiles are enriched with key contact details, including work emails, phone numbers, and physical addresses, ensuring direct access to decision-makers.
Industry-Specific Data: Tailored datasets for sectors such as financial services, manufacturing, technology, healthcare, and energy, among others. Each dataset is customized to meet the unique needs of industry professionals and analysts.
Real-Time Accuracy: With continuous updates powered by AI-driven validation, our financial data maintains a 99% accuracy rate, ensuring you have access to the most reliable and up-to-date information available.
Compliance and Security: All data is collected and processed in strict adherence to global compliance standards, including GDPR, ensuring ethical and lawful usage.
Why Choose Success.ai for Company Financial Data?
Best Price Guarantee: We pride ourselves on offering the most competitive pricing in the industry, ensuring you receive unparalleled value for comprehensive financial data.
AI-Validated Accuracy: Our advanced AI algorithms meticulously verify every data point to ensure precision and reliability, helping you avoid costly errors in your financial decision-making.
Customized Data Solutions: Whether you need data for a specific region, industry, or type of business, we tailor our datasets to align perfectly with your requirements.
Scalable Data Access: From small startups to global enterprises, our platform caters to businesses of all sizes, delivering scalable solutions to suit your operational needs.
Comprehensive Use Cases for Financial Data:
Leverage our detailed financial profiles to create accurate budgets, forecasts, and strategic plans. Gain insights into competitors’ financial health and market positions to make data-driven decisions.
Access key financial details and contact information to streamline your M&A processes. Identify potential acquisition targets or partners with verified profiles and financial data.
Evaluate the financial performance of public and private companies for informed investment decisions. Use our data to identify growth opportunities and assess risk factors.
Enhance your sales outreach by targeting CFOs, financial analysts, and other decision-makers with verified contact details. Utilize accurate email and phone data to increase conversion rates.
Understand market trends and financial benchmarks with our industry-specific datasets. Use the data for competitive analysis, benchmarking, and identifying market gaps.
APIs to Power Your Financial Strategies:
Enrichment API: Integrate real-time updates into your systems with our Enrichment API. Keep your financial data accurate and current to drive dynamic decision-making and maintain a competitive edge.
Lead Generation API: Supercharge your lead generation efforts with access to verified contact details for key financial decision-makers. Perfect for personalized outreach and targeted campaigns.
Tailored Solutions for Industry Professionals:
Financial Services Firms: Gain detailed insights into revenue streams, funding rounds, and operational costs for competitor analysis and client acquisition.
Corporate Finance Teams: Enhance decision-making with precise data on industry trends and benchmarks.
Consulting Firms: Deliver informed recommendations to clients with access to detailed financial datasets and key stakeholder profiles.
Investment Firms: Identify potential investment opportunities with verified data on financial performance and market positioning.
What Sets Success.ai Apart?
Extensive Database: Access detailed financial data for 70M+ companies worldwide, including small businesses, startups, and large corporations.
Ethical Practices: Our data collection and processing methods are fully comp...
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This dataset provides values for MANUFACTURING PMI reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
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This synthetic dataset simulates two years of transactional data for a multinational fashion retailer, featuring:
- 📈 4+ million sales records
- 🏪 35 stores across 7 countries:
🇺🇸 United States | 🇨🇳 China | 🇩🇪 Germany | 🇬🇧 United Kingdom | 🇫🇷 France | 🇪🇸 Spain | 🇵🇹 Portugal
Currencies Covered:
Each transaction includes detailed currency information, covering multiple currencies:
💵 USD (United States) | 💶 EUR (Eurozone) | 💴 CNY (China) | 💷 GBP (United Kingdom)
🌐 Geographic Sales Comparison
Gain insights into how sales performance varies between regions and countries, and identify trends that drive success in different markets.
👥 Analyze Staffing and Performance
Evaluate store staffing ratios and analyze the impact of employee performance on store success.
🛍️ Customer Behavior and Segmentation
Understand regional customer preferences, analyze demographic factors such as age and occupation, and segment customers based on their purchasing habits.
💱 Multi-Currency Analysis
Explore how transactions in different currencies (USD, EUR, CNY, GBP) are handled, analyze currency exchange effects, and compare sales across regions using multiple currencies.
👗 Product Trends
Assess how product categories (e.g., Feminine, Masculine, Children) and specific product attributes (size, color) perform across different regions.
🎯 Pricing and Discount Analysis
Study how different pricing models and discounts affect sales and customer decisions across diverse geographies.
📊 Advanced Cross-Country & Currency Analysis
Conduct complex, multi-dimensional analytics that interconnect countries, currencies, and sales data, identifying hidden correlations between economic factors, regional demand, and financial performance.
Generated using algorithms, it simulates real-world retail dynamics while ensuring privacy.
This dataset is an ideal resource for retail analysts, data scientists, and business intelligence professionals aiming to explore multinational retail data, optimize operations, and uncover new insights into customer behavior, sales trends, and employee efficiency.
The number of Instagram users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 2.1 million users (+7.02 percent). After the ninth consecutive increasing year, the Instagram user base is estimated to reach 32 million users and therefore a new peak in 2028. Notably, the number of Instagram users of was continuously increasing over the past years.User figures, shown here with regards to the platform instagram, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).
MealMe offers in-depth restaurant menu data, including prices, from the top 100,000 restaurants across the USA and Canada. Our proprietary technology collects accurate, real-time menu and pricing information, enabling businesses to make data-driven decisions in competitive intelligence, pricing optimization, and market research. With comprehensive coverage that spans major restaurant platforms and chains, MealMe ensures your business has access to the most reliable data to excel in a rapidly evolving industry.
Platforms and Restaurants Covered: MealMe's database includes data from leading restaurant platforms such as UberEats, Postmates, ToastTakeout, SkipTheDishes, Square, Appfront, Olo, TouchBistro, and Clover, as well as direct menu data from major restaurant chains including Raising Cane’s, Panda Express, Popeyes, Burger King, and Subway. This extensive coverage ensures a detailed view of the market, helping businesses monitor trends, pricing, and availability across a broad spectrum of restaurant types and sizes.
Key Features: Comprehensive Menu Data: Access detailed menu information, including item descriptions, categories, sizes, and customizations. Real-Time Pricing: Monitor up-to-date menu prices for accurate competitive analysis. Restaurant-Specific Insights: Analyze individual restaurant chains such as Raising Cane’s and Panda Express, or platforms like UberEats, for market trends and pricing strategies. Cross-Platform Analysis: Compare menu items and pricing across platforms like ToastTakeout, Olo, and SkipTheDishes for a holistic industry view. Regional Data: Understand geographic variations in menu offerings and pricing across the USA and Canada.
Use Cases: Competitive Intelligence: Track menu offerings, pricing strategies, and seasonal trends across platforms like UberEats and Postmates or chains like Popeyes and Subway. Market Research: Identify gaps in the market by analyzing menus and pricing from top restaurants. Pricing Optimization: Use real-time pricing data to inform dynamic pricing strategies and promotions. Trend Monitoring: Stay ahead by tracking popular menu items, regional preferences, and emerging food trends. Platform Analysis: Assess how restaurants perform across delivery platforms such as SkipTheDishes, Olo, and Square. Industries Benefiting from Our Data Restaurant Chains: Optimize menu offerings and pricing strategies with detailed competitor data. Food Delivery Platforms: Benchmark menu pricing and availability across competitive platforms. Market Research Firms: Conduct detailed analyses to identify opportunities and market trends. AI & Analytics Companies: Power recommendation engines and predictive models with robust menu data. Consumer Apps: Enhance app experiences with accurate menu and pricing data. Data Delivery and Integration
MealMe offers flexible integration options to ensure seamless access to our comprehensive menu data. Whether you need bulk exports for in-depth research or real-time updates via API, our solutions are designed to scale with your business needs.
Why Choose MealMe? Extensive Coverage: Menu data from 100,000+ restaurants, including major chains like Burger King and Raising Cane’s. Real-Time Accuracy: Up-to-date pricing and menu details for actionable insights. Customizable Solutions: Tailored datasets to meet your specific business objectives. Proven Expertise: Trusted by top companies for delivering reliable, actionable data. MealMe empowers businesses with the data needed to thrive in a competitive restaurant and food delivery market. For more information or to request a demo, contact us today!
The number of LinkedIn users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 1.5 million users (+4.51 percent). After the eighth consecutive increasing year, the LinkedIn user base is estimated to reach 34.7 million users and therefore a new peak in 2028. User figures, shown here with regards to the platform LinkedIn, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).
Version 11.1 Release Date: August 22, 2022
The Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. These data and their derivatives are the only international boundary lines approved for U.S. Government use. They reflect U.S. Government policy, and not necessarily de facto limits of control. This dataset is a National Geospatial Data Asset.
Sources for these data include treaties, relevant maps, and data from boundary commissions and national mapping agencies. Where available, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery of the data involves analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground.
The dataset uses the following attributes: Attribute Name Explanation Country Code Country-level codes are from the Geopolitical Entities, Names, and Codes Standard (GENC). The Q2 code denotes a line representing a boundary associated with an area not in GENC. Country Names Names approved by the U.S. Board on Geographic Names (BGN). Names for lines associated with a Q2 code are descriptive and are not necessarily BGN-approved. Label Required text label for the line segment where scale permits Rank/Status Rank 1: International Boundary Rank 2: Other Line of International Separation Rank 3: Special Line Notes Explanation of any applicable special circumstances Cartographic Usage Depiction of the LSIB requires a visual differentiation between the three categories of boundaries: International Boundaries (Rank 1), Other Lines of International Separation (Rank 2), and Special Lines (Rank 3). Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary. Additional cartographic information can be found in Guidance Bulletins (https://hiu.state.gov/data/cartographic_guidance_bulletins/) published by the Office of the Geographer and Global Issues. Please direct inquiries to internationalboundaries@state.gov.
The lines in the LSIB dataset are the product of decades of collaboration between geographers at the Department of State and the National Geospatial-Intelligence Agency with contributions from the Central Intelligence Agency and the UK Defence Geographic Centre. Attribution is welcome: U.S. Department of State, Office of the Geographer and Global Issues.
This version of the LSIB contains changes and accuracy refinements for the following line segments. These changes reflect improvements in spatial accuracy derived from newly available source materials, an ongoing review process, or the publication of new treaties or agreements. Changes to lines include: • Akrotiri (UK) / Cyprus • Albania / Montenegro • Albania / Greece • Albania / North Macedonia • Armenia / Turkey • Austria / Czechia • Austria / Slovakia • Austria / Hungary • Austria / Slovenia • Austria / Germany • Austria / Italy • Austria / Switzerland • Azerbaijan / Turkey • Azerbaijan / Iran • Belarus / Latvia • Belarus / Russia • Belarus / Ukraine • Belarus / Poland • Bhutan / India • Bhutan / China • Bulgaria / Turkey • Bulgaria / Romania • Bulgaria / Serbia • Bulgaria / Romania • China / Tajikistan • China / India • Croatia / Slovenia • Croatia / Hungary • Croatia / Serbia • Croatia / Montenegro • Czechia / Slovakia • Czechia / Poland • Czechia / Germany • Finland / Russia • Finland / Norway • Finland / Sweden • France / Italy • Georgia / Turkey • Germany / Poland • Germany / Switzerland • Greece / North Macedonia • Guyana / Suriname • Hungary / Slovenia • Hungary / Serbia • Hungary / Romania • Hungary / Ukraine • Iran / Turkey • Iraq / Turkey • Italy / Slovenia • Italy / Switzerland • Italy / Vatican City • Italy / San Marino • Kazakhstan / Russia • Kazakhstan / Uzbekistan • Kosovo / north Macedonia • Kosovo / Serbia • Kyrgyzstan / Tajikistan • Kyrgyzstan / Uzbekistan • Latvia / Russia • Latvia / Lithuania • Lithuania / Poland • Lithuania / Russia • Moldova / Ukraine • Moldova / Romania • Norway / Russia • Norway / Sweden • Poland / Russia • Poland / Ukraine • Poland / Slovakia • Romania / Ukraine • Romania / Serbia • Russia / Ukraine • Syria / Turkey • Tajikistan / Uzbekistan
This release also contains topology fixes, land boundary terminus refinements, and tripoint adjustments.
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