48 datasets found
  1. d

    Company Data | 6.7MM+ Total Companies | Company Name, Industry, Employees,...

    • datarade.ai
    .json, .csv, .xls
    Updated Jun 8, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Salutary Data (2023). Company Data | 6.7MM+ Total Companies | Company Name, Industry, Employees, Revenue, Website, Addresses + More [Dataset]. https://datarade.ai/data-products/salutary-data-company-data-4m-total-companies-company-salutary-data
    Explore at:
    .json, .csv, .xlsAvailable download formats
    Dataset updated
    Jun 8, 2023
    Dataset authored and provided by
    Salutary Data
    Area covered
    United States of America
    Description

    Salutary Data is a boutique, B2B contact and company data provider that's committed to delivering high quality data for sales intelligence, lead generation, marketing, recruiting / HR, identity resolution, and ML / AI. Our database currently consists of 148MM+ highly curated B2B Contacts ( US only), along with over 4M+ companies, and is updated regularly to ensure we have the most up-to-date information.

    We can enrich your in-house data ( CRM Enrichment, Lead Enrichment, etc.) and provide you with a custom dataset ( such as a lead list) tailored to your target audience specifications and data use-case. We also support large-scale data licensing to software providers and agencies that intend to redistribute our data to their customers and end-users.

    What makes Salutary unique? - We offer our clients a truly unique, one-stop aggregation of the best-of-breed quality data sources. Our supplier network consists of numerous, established high quality suppliers that are rigorously vetted. - We leverage third party verification vendors to ensure phone numbers and emails are accurate and connect to the right person. Additionally, we deploy automated and manual verification techniques to ensure we have the latest job information for contacts. - We're reasonably priced and easy to work with.

    Products: API Suite Web UI Full and Custom Data Feeds

    Services: Data Enrichment - We assess the fill rate gaps and profile your customer file for the purpose of appending fields, updating information, and/or rendering net new “look alike” prospects for your campaigns. ABM Match & Append - Send us your domain or other company related files, and we’ll match your Account Based Marketing targets and provide you with B2B contacts to campaign. Optionally throw in your suppression file to avoid any redundant records. Verification (“Cleaning/Hygiene”) Services - Address the 2% per month aging issue on contact records! We will identify duplicate records, contacts no longer at the company, rid your email hard bounces, and update/replace titles or phones. This is right up our alley and levers our existing internal and external processes and systems.

  2. Google: annual advertising revenue 2001-2024

    • statista.com
    Updated Feb 5, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Google: annual advertising revenue 2001-2024 [Dataset]. https://www.statista.com/statistics/266249/advertising-revenue-of-google/
    Explore at:
    Dataset updated
    Feb 5, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    In 2023, Google's ad revenue amounted to 264.59 billion U.S. dollars. The company generates advertising revenue through its Google Ads platform, which enables advertisers to display ads, product listings and service offerings across Google’s extensive ad network (properties, partner sites, and apps) to web users. Google advertising Advertising accounts for the majority of Google’s revenue, which amounted to a total of 305.63 billion U.S. dollars in 2023. The majority of Google's advertising revenue comes from search advertising. Google market share These revenue figures come as no surprise, as Google accounts for the majority of the online and mobile search market worldwide. As of September 2023, Google was responsible for more than 84 percent of global desktop search traffic. The company holds a market share of more than 80 percent in a wide range of digital markets, having little to no domestic competition in many of them. China, Russia, and to a certain extent, Japan, are some of the few notable exceptions, where local products are more preferred.

  3. A

    Employee Earnings Report

    • data.boston.gov
    csv
    Updated Feb 28, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Office of Human Resources (2025). Employee Earnings Report [Dataset]. https://data.boston.gov/dataset/employee-earnings-report
    Explore at:
    csv, csv(3372412), csv(2597411), csv(2535798), csv(2407767), csv(2519912), csv(1967674), csv(2780939), csv(13225)Available download formats
    Dataset updated
    Feb 28, 2025
    Dataset authored and provided by
    Office of Human Resources
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    Each year, the City of Boston publishes payroll data for employees. This dataset contains employee names, job details, and earnings information including base salary, overtime, and total compensation for employees of the City.

    See the "Payroll Categories" document below for an explanation of what types of earnings are included in each category.

  4. i

    Website Speed Test Market - In-Deep Analysis Focusing on Market Share

    • imrmarketreports.com
    Updated Aug 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Swati Kalagate; Akshay Patil; Vishal Kumbhar (2022). Website Speed Test Market - In-Deep Analysis Focusing on Market Share [Dataset]. https://www.imrmarketreports.com/reports/website-speed-test-market
    Explore at:
    Dataset updated
    Aug 2022
    Dataset provided by
    IMR Market Reports
    Authors
    Swati Kalagate; Akshay Patil; Vishal Kumbhar
    License

    https://www.imrmarketreports.com/privacy-policy/https://www.imrmarketreports.com/privacy-policy/

    Description

    Report of Website Speed Test Market is currently supplying a comprehensive analysis of many things which are liable for economy growth and factors which could play an important part in the increase of the marketplace in the prediction period. The record of Website Speed Test Industry is providing the thorough study on the grounds of market revenue discuss production and price happened. The report also provides the overview of the segmentation on the basis of area, contemplating the particulars of earnings and sales pertaining to marketplace.

  5. m

    Data from: Median Household Income

    • miamicountyks.org
    • weyburneconomicdevelopment.com
    • +73more
    Updated Dec 15, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2022). Median Household Income [Dataset]. https://www.miamicountyks.org/874/City-of-Louisburg
    Explore at:
    Dataset updated
    Dec 15, 2022
    Description

    The median income indicates the income bracket separating the income earners into two halves of equal size.

  6. b

    Facebook Revenue and Usage Statistics (2025)

    • businessofapps.com
    Updated Aug 8, 2017
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Business of Apps (2017). Facebook Revenue and Usage Statistics (2025) [Dataset]. https://www.businessofapps.com/data/facebook-statistics/
    Explore at:
    Dataset updated
    Aug 8, 2017
    Dataset authored and provided by
    Business of Apps
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    Facebook probably needs no introduction; nonetheless, here is a quick history of the company. The world’s biggest and most-famous social network was launched by Mark Zuckerberg while he was a...

  7. Global retail e-commerce sales 2022-2028

    • statista.com
    Updated Jun 24, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Global retail e-commerce sales 2022-2028 [Dataset]. https://www.statista.com/statistics/379046/worldwide-retail-e-commerce-sales/
    Explore at:
    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.

  8. m

    Graham Holdings Co - Net-Income-Applicable-To-Common-Shares

    • macro-rankings.com
    csv, excel
    Updated Mar 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    macro-rankings (2025). Graham Holdings Co - Net-Income-Applicable-To-Common-Shares [Dataset]. https://www.macro-rankings.com/Markets/Stocks?Entity=GHC.US&Item=Net-Income-Applicable-To-Common-Shares
    Explore at:
    excel, csvAvailable download formats
    Dataset updated
    Mar 18, 2025
    Dataset authored and provided by
    macro-rankings
    License

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

    Area covered
    United States
    Description

    Net-Income-Applicable-To-Common-Shares Time Series for Graham Holdings Co. Graham Holdings Company, through its subsidiaries, operates as a diversified holding company in the United States and internationally. The company provides test preparation services and materials; professional training and exam preparation for professional certifications and licensures; and non-academic operations support services to the Purdue University Global; operations support services for online courses and programs; training and test preparation services for accounting and financial services professionals; language training, academic preparation programs, and preparation for proficiency exams; and A-level examination services, as well as operates colleges, business school, higher education institution, and an online learning institution. It also owns and operates television stations, restaurants, and entertainment venues; engages in the financial training and automobile dealerships business; offers social media management tools to connect newsrooms with their users; produces Foreign Policy magazine and ForeignPolicy.com website; and publishes Slate, an online magazine, as well as French-language news magazine website at slate.fr. In addition, the company provides social media marketing solutions; home health, hospice, and palliative services; burners, igniters, dampers, and controls; screw jacks, linear actuators, and related linear motion products and lifting systems; pressure impregnated kiln-dried lumber and plywood products; digital advertising services; power charging and data systems, industrial and commercial indoor lighting solutions, and electrical components and assemblies; valet repair services; in-home aesthetics; and physician and healthcare software-as-a-services, as well as operates pharmacy. The company was formerly known as The Washington Post Company and changed its name to Graham Holdings Company in November 2013. Graham Holdings Company was founded in 1877 and is based in Arlington, Virginia.

  9. u

    National Income Dynamics Study - Coronavirus Rapid Mobile Survey 2021, Wave...

    • datafirst.uct.ac.za
    Updated Mar 11, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Nic Spaull - Ronelle Burger - Rulof Burger - David Carel - Reza Daniels - Nwabisa Makaluza - Dorrit Posel - Vimal Ranchhod - Servaas van der Berg - Gabrielle Wills (2025). National Income Dynamics Study - Coronavirus Rapid Mobile Survey 2021, Wave 4 - South Africa [Dataset]. https://www.datafirst.uct.ac.za/dataportal/index.php/catalog/867
    Explore at:
    Dataset updated
    Mar 11, 2025
    Dataset authored and provided by
    Nic Spaull - Ronelle Burger - Rulof Burger - David Carel - Reza Daniels - Nwabisa Makaluza - Dorrit Posel - Vimal Ranchhod - Servaas van der Berg - Gabrielle Wills
    Time period covered
    2020 - 2021
    Area covered
    South Africa
    Description

    Abstract

    The National Income Dynamics Study - Coronavirus Rapid Mobile Survey 2020 investigates the socioeconomic impacts of the national lockdown associated with the State of Disaster declared in South Africa in March 2020, and the social and economic consequences in South Africa of the global Coronavirus pandemic. NIDS-CRAM forms part of a broader study called the Coronavirus Rapid Mobile Survey (CRAM) which aims to inform policy using rapid reliable research on income, employment and welfare in South Africa, in the context of the global Coronavirus pandemic. The study is run by researchers from the University of Stellenbosch, University of Cape Town (UCT) and University of the Witwatersrand (Wits). The NIDS-CRAM survey data collection and production operations were implemented by the Southern Africa Labour and Development Research Unit (SALDRU) at UCT. The data is collected with Computer Assisted Telephone Interviewing (CATI), with data collection repeated over several months.

    Geographic coverage

    The survey had national coverage. As NIDS was only designed to be nationally representative, it is inadvisable to use the NIDS-CRAM data to calculate provincial or regional totals.

    Analysis unit

    Households and individuals

    Universe

    The universe of the study is South Africans 18 years old or older.

    Kind of data

    Survey data

    Sampling procedure

    The sample frame for NIDS-CRAM is the NIDS Wave 5 CSMs and TSMs who were 18 years or older at the time of the NIDS-CRAM Wave 1 fieldwork preparation in April 2020. The sample was drawn using a stratified sampling design. No attempt was made to check whether successfully re-interviewed individuals resided in the same households as they did in Wave 5. In the survey, individuals from larger households were more likely to be sampled than individuals from smaller households.

    Mode of data collection

    Computer Assisted Telephone Interview

    Research instrument

    Though NIDS-CRAM is a follow-up with NIDS Wave 5 respondents, the NIDS-CRAM survey uses a much shorter questionnaire, with a focus on the Coronavirus pandemic and the national lockdown. The questionnaire was changed slightly across waves and data users should check the questionnaires for each wave when using the data.

  10. f

    Car Tax Calculation Dataset

    • fleetnews.co.uk
    web interactive
    Updated Aug 12, 2011
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Fleet News (2011). Car Tax Calculation Dataset [Dataset]. https://www.fleetnews.co.uk/cars/car-tax-calculator/
    Explore at:
    web interactiveAvailable download formats
    Dataset updated
    Aug 12, 2011
    Dataset authored and provided by
    Fleet News
    Variables measured
    VED, Fuel Cost, SMR Costs, Class 1A NIC, Depreciation, CO2 Emissions, Running Costs, Residual Value, Benefit in Kind, List Price (P11D), and 8 more
    Description

    A dataset of car tax calculations for company cars by operating cycle, manufacturer, model, and derivative.

  11. Most popular travel and tourism websites worldwide 2025

    • statista.com
    • ai-chatbox.pro
    Updated Aug 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Most popular travel and tourism websites worldwide 2025 [Dataset]. https://www.statista.com/statistics/1215457/most-visited-travel-and-tourism-websites-worldwide/
    Explore at:
    Dataset updated
    Aug 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2025
    Area covered
    Worldwide
    Description

    In July 2025, booking.com was the most visited travel and tourism website worldwide. That month, Booking’s web page recorded almost *** million visits. Tripadvisor.com and wetter.com followed in the ranking, with roughly *** million and *** million visits, respectively. Popular online travel agencies in the U.S. Online travel agencies (OTAs), such as Booking.com and Expedia, offer a wide variety of services, including online hotel bookings, flight reservations, and car rentals. According to the Statista Consumer Insights Global survey, when looking at flight search engine online bookings by brand in the United States, Booking.com and Expedia were the most popular options when it came to making online flight reservations in 2025. When focusing on hotel and private accommodation online bookings in the U.S., Booking.com was again the most popular brand, followed by Airbnb, Expedia, and Hotels.com. Booking Holdings vs. Expedia Group Booking.com is one of the most popular sites of the online travel group Booking Holdings, the leading online travel agency worldwide based on revenue, that also owns brands like Priceline, Kayak, and Agoda. In 2024, Booking Holdings' revenue amounted to almost ** billion U.S. dollars, the highest figure reported by the company to date. Meanwhile, global revenue of Expedia Group, which manages brands like Expedia, Hotels.com, and Vrbo, reached nearly ** billion U.S. dollars that year.

  12. y

    YOUTAX India Consulting Pvt. Ltd

    • youbuz.in
    html
    Updated Oct 8, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    YOUTAX India Consulting Pvt. Ltd (2018). YOUTAX India Consulting Pvt. Ltd [Dataset]. https://youbuz.in/
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Oct 8, 2018
    Dataset provided by
    https://youbuz.in/
    Authors
    YOUTAX India Consulting Pvt. Ltd
    Area covered
    Description

    The team at the firm has dedicated and experienced professionals and associates like Chartered Accountants, Company Secretary and Consultants to provide end to end services to your business. Founded in 2018 by Mr. Nandkishor And Mrs. Sonali Devadnye, YOUTAX INDIA CONSULTING PRIVATE LIMITED has come a long way from its beginnings in Hadapsar Pune. When they first started out, their passion for providing in time delivery of quality services in the field of TAX so that YOUTAX INDIA CONSULTING PRIVATE LIMITED can offer you quality services for your business for future growth. We now serve customers all over Maharashtra.

  13. 2010 American Community Survey: B19326 | MEDIAN INCOME IN THE PAST 12 MONTHS...

    • data.census.gov
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ACS, 2010 American Community Survey: B19326 | MEDIAN INCOME IN THE PAST 12 MONTHS (IN 2010 INFLATION-ADJUSTED DOLLARS) BY SEX BY WORK EXPERIENCE IN THE PAST 12 MONTHS FOR THE POPULATION 15 YEARS AND OVER WITH INCOME (ACS 5-Year Estimates Selected Population Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT5YSPT2010.B19326?q=Earnings+(Individuals)&t=Population+Total&g=050XX00US06055,06001,06013,06081,06095,06041,06085,06075,06097
    Explore at:
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2010
    Description

    Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2010, the 2010 Census provides the official counts of the population and housing units for the nation, states, counties, cities and towns. For 2006 to 2009, the Population Estimates Program provides intercensal estimates of the population for the nation, states, and counties..Explanation of Symbols:.An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2000 data. Boundaries for urban areas have not been updated since Census 2000. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2006-2010 American Community Survey (ACS) data generally reflect the December 2009 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..The methodology for calculating median income and median earnings changed between 2008 and 2009. Medians over $75,000 were most likely affected. The underlying income and earning distribution now uses $2,500 increments up to $250,000 for households, non-family households, families, and individuals and employs a linear interpolation method for median calculations. Before 2009 the highest income category was $200,000 for households, families and non-family households ($100,000 for individuals) and portions of the income and earnings distribution contained intervals wider than $2,500. Those cases used a Pareto Interpolation Method..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2006-2010 American Community Survey

  14. Rates of Income Tax

    • gov.uk
    • s3.amazonaws.com
    Updated Jun 26, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    HM Revenue & Customs (2025). Rates of Income Tax [Dataset]. https://www.gov.uk/government/statistics/rates-of-income-statistics
    Explore at:
    Dataset updated
    Jun 26, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    HM Revenue & Customs
    Description

    These statistics are for tax year 1990 to 1991, to tax year 2025 to 2026.

    For previous years please see the https://webarchive.nationalarchives.gov.uk/ukgwa/+/http://www.hmrc.gov.uk/stats/tax_structure/menu.htm" class="govuk-link">National Archives website.

  15. 2011 American Community Survey: B19049 | MEDIAN HOUSEHOLD INCOME IN THE PAST...

    • data.census.gov
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ACS, 2011 American Community Survey: B19049 | MEDIAN HOUSEHOLD INCOME IN THE PAST 12 MONTHS (IN 2011 INFLATION-ADJUSTED DOLLARS) BY AGE OF HOUSEHOLDER (ACS 5-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT5Y2011.B19049?tid=ACSDT5Y2011.B19049
    Explore at:
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2011
    Description

    Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2000 data. Boundaries for urban areas have not been updated since Census 2000. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2007-2011 American Community Survey (ACS) data generally reflect the December 2009 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..The methodology for calculating median income and median earnings changed between 2008 and 2009. Medians over $75,000 were most likely affected. The underlying income and earning distribution now uses $2,500 increments up to $250,000 for households, non-family households, families, and individuals and employs a linear interpolation method for median calculations. Before 2009 the highest income category was $200,000 for households, families and non-family households ($100,000 for individuals) and portions of the income and earnings distribution contained intervals wider than $2,500. Those cases used a Pareto Interpolation Method..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2007-2011 American Community Survey

  16. 2011 American Community Survey: S2409 | CLASS OF WORKER BY SEX AND MEDIAN...

    • data.census.gov
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ACS, 2011 American Community Survey: S2409 | CLASS OF WORKER BY SEX AND MEDIAN EARNINGS IN THE PAST 12 MONTHS (IN 2011 INFLATION-ADJUSTED DOLLARS) FOR THE FULL-TIME, YEAR-ROUND CIVILIAN EMPLOYED POPULATION 16 YEARS AND OVER (ACS 5-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/table/ACSST5Y2011.S2409?q=&t=Age+and+Sex:Earnings+(Individuals):Income+and+Earnings&g=050XX00US37037&y=2011
    Explore at:
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2011
    Description

    Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2000 data. Boundaries for urban areas have not been updated since Census 2000. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2007-2011 American Community Survey (ACS) data generally reflect the December 2009 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..The Class of Worker status "unpaid family workers" may have earnings. Earnings reflect any earnings from all jobs held during the 12 months prior to the ACS interview. The Class of Worker status reflects the job or business held the week prior to the ACS interview, or the last job held by the respondent..The methodology for calculating median income and median earnings changed between 2008 and 2009. Medians over $75,000 were most likely affected. The underlying income and earning distribution now uses $2,500 increments up to $250,000 for households, non-family households, families, and individuals and employs a linear interpolation method for median calculations. Before 2009 the highest income category was $200,000 for households, families and non-family households ($100,000 for individuals) and portions of the income and earnings distribution contained intervals wider than $2,500. Those cases used a Pareto Interpolation Method..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2007-2011 American Community Survey

  17. e

    Mobile Gacha Game Revenue Analytics

    • revenue.ennead.cc
    Updated Dec 30, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2024). Mobile Gacha Game Revenue Analytics [Dataset]. https://revenue.ennead.cc/revenue
    Explore at:
    Dataset updated
    Dec 30, 2024
    Description

    Comprehensive revenue analytics and insights for mobile gacha games

  18. m

    Property Tax Data and Statistics

    • mass.gov
    Updated May 14, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Division of Local Services (2022). Property Tax Data and Statistics [Dataset]. https://www.mass.gov/lists/property-tax-data-and-statistics
    Explore at:
    Dataset updated
    May 14, 2022
    Dataset authored and provided by
    Division of Local Services
    Area covered
    Massachusetts
    Description

    Data, statistics and adopted local options related to property taxes

  19. 2011 American Community Survey: B19019 | MEDIAN HOUSEHOLD INCOME IN THE PAST...

    • data.census.gov
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ACS, 2011 American Community Survey: B19019 | MEDIAN HOUSEHOLD INCOME IN THE PAST 12 MONTHS (IN 2011 INFLATION-ADJUSTED DOLLARS) BY HOUSEHOLD SIZE (ACS 5-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT5Y2011.B19019
    Explore at:
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2011
    Description

    Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2000 data. Boundaries for urban areas have not been updated since Census 2000. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2007-2011 American Community Survey (ACS) data generally reflect the December 2009 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..The methodology for calculating median income and median earnings changed between 2008 and 2009. Medians over $75,000 were most likely affected. The underlying income and earning distribution now uses $2,500 increments up to $250,000 for households, non-family households, families, and individuals and employs a linear interpolation method for median calculations. Before 2009 the highest income category was $200,000 for households, families and non-family households ($100,000 for individuals) and portions of the income and earnings distribution contained intervals wider than $2,500. Those cases used a Pareto Interpolation Method..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2007-2011 American Community Survey

  20. G

    Old Age Security (OAS) - Table of Benefit Amounts by marital status and...

    • open.canada.ca
    csv, pdf, xlsx
    Updated Jul 2, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Employment and Social Development Canada (2025). Old Age Security (OAS) - Table of Benefit Amounts by marital status and income level [Dataset]. https://open.canada.ca/data/en/dataset/dfa4daf1-669e-4514-82cd-982f27707ed0
    Explore at:
    xlsx, csv, pdfAvailable download formats
    Dataset updated
    Jul 2, 2025
    Dataset provided by
    Employment and Social Development Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Time period covered
    Jul 1, 2025 - Sep 30, 2025
    Description

    This dataset provides information on Benefits Amounts for Income Supplement and the Allowances according to income level and marital status. This is updated on a quarterly basis. The following tables of amounts will provide you with the amount of your monthly benefit, which will be based on your age, income level and marital status. The dataset is updated for July - September 2025 quarter.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Salutary Data (2023). Company Data | 6.7MM+ Total Companies | Company Name, Industry, Employees, Revenue, Website, Addresses + More [Dataset]. https://datarade.ai/data-products/salutary-data-company-data-4m-total-companies-company-salutary-data

Company Data | 6.7MM+ Total Companies | Company Name, Industry, Employees, Revenue, Website, Addresses + More

Explore at:
.json, .csv, .xlsAvailable download formats
Dataset updated
Jun 8, 2023
Dataset authored and provided by
Salutary Data
Area covered
United States of America
Description

Salutary Data is a boutique, B2B contact and company data provider that's committed to delivering high quality data for sales intelligence, lead generation, marketing, recruiting / HR, identity resolution, and ML / AI. Our database currently consists of 148MM+ highly curated B2B Contacts ( US only), along with over 4M+ companies, and is updated regularly to ensure we have the most up-to-date information.

We can enrich your in-house data ( CRM Enrichment, Lead Enrichment, etc.) and provide you with a custom dataset ( such as a lead list) tailored to your target audience specifications and data use-case. We also support large-scale data licensing to software providers and agencies that intend to redistribute our data to their customers and end-users.

What makes Salutary unique? - We offer our clients a truly unique, one-stop aggregation of the best-of-breed quality data sources. Our supplier network consists of numerous, established high quality suppliers that are rigorously vetted. - We leverage third party verification vendors to ensure phone numbers and emails are accurate and connect to the right person. Additionally, we deploy automated and manual verification techniques to ensure we have the latest job information for contacts. - We're reasonably priced and easy to work with.

Products: API Suite Web UI Full and Custom Data Feeds

Services: Data Enrichment - We assess the fill rate gaps and profile your customer file for the purpose of appending fields, updating information, and/or rendering net new “look alike” prospects for your campaigns. ABM Match & Append - Send us your domain or other company related files, and we’ll match your Account Based Marketing targets and provide you with B2B contacts to campaign. Optionally throw in your suppression file to avoid any redundant records. Verification (“Cleaning/Hygiene”) Services - Address the 2% per month aging issue on contact records! We will identify duplicate records, contacts no longer at the company, rid your email hard bounces, and update/replace titles or phones. This is right up our alley and levers our existing internal and external processes and systems.

Search
Clear search
Close search
Google apps
Main menu