41 datasets found
  1. Fortune 500 - 2017

    • data.world
    csv, zip
    Updated Dec 14, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Aurielle Perlmann (2022). Fortune 500 - 2017 [Dataset]. https://data.world/aurielle/fortune-500-2017
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Dec 14, 2022
    Dataset provided by
    data.world, Inc.
    Authors
    Aurielle Perlmann
    Description

    aurielle is using data.world to share Fortune 500 - 2017 data

  2. 2023 Fortune 1000 Companies

    • kaggle.com
    Updated Sep 8, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    k04dRunn3r (2023). 2023 Fortune 1000 Companies [Dataset]. https://www.kaggle.com/datasets/jeannicolasduval/2023-fortune-1000-companies-info
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 8, 2023
    Dataset provided by
    Kaggle
    Authors
    k04dRunn3r
    Description

    Data from Fortune 500's 2023 ranking.
    Includes data on top 1000 companies w/ additional info (Stock symbol/*ticker*, CEO name).

    Update (New dataset): 2024 Fortune 1000 Companies

    What Is the Fortune 1000?

    From Investopedia:

    The Fortune 1000 is an annual list of the 1000 largest American companies maintained by the popular magazine Fortune Fortune ranks the eligible companies by revenue generated from core operations, discounted operations, and consolidated subsidiaries Since revenue is the basis for inclusion, every company is authorized to operate in the United States and files a 10-K or comparable financial statement with a government agency -- .

    Project Background

    Fortune magazine publishes this list every year and some lists can be found from different sources. From looking at this year's available datasets, some features were missing or could not be found. This was built from scraping the standard features as well as what's included on Company Info (such as CEO, Ticker and website) from the Fortune magazine website. Details on how the data was generated can be found on this notebook where a few of the features were also visualized.

    The source code from the 2023 fortune 500 Ranking includes 1000 companies. A reference page (slug) to additional info is included for each companies which were also scrapped to complete the dataset.

    The Dataset

    Available formats: csv, parquet

    Features are follows:

    [Note: References to datatypes are relevant when using the parquet file; Labels refer to the original website names]

    • Rank
        dtype: int64; Label: Rank
    • Company
        dtype: object; Label: Company
    • Ticker
        dtype: object; Label: Ticker
    • Sector
        dtype: category; Label: Sector
    • Industry
        dtype: category; Label: Industry
    • Profitable
        dtype: category; Label: Profitable
    • Founder_is_CEO
        dtype: category; Label: Founder is CEO
    • FemaleCEO
        dtype: category; Label: Female CEO
    • Growth_in_Jobs
        dtype: category; Label: Growth in Jobs
    • Change_in_Rank
        dtype: float64; Label: Change in Rank (Full 1000)
    • Gained_in_Rank
        dtype: category; Label: Gained in Rank
    • Dropped_in_Rank
        dtype: category; Label: Dropped in Rank
    • Newcomer_to_the_Fortune500
        dtype: category; Label: Newcomer to the Fortune 500
    • Global500
        dtype: category; Label: Global 500
    • Best_Companies
        dtype: category; Label: Best Companies
    • Number_of_employees
        dtype: int64; Label: Employees
    • MarketCap_March31_M
        dtype: float64; Label: Market Value — as of March 31, 2023 ($M)
    • Revenues_M
        dtype: int64; Label: Revenues ($M)
    • RevenuePercentChange
        dtype: float64; Label: Revenue Percent Change
    • Profits_M
        dtype: int64; Label: Profits ($M)
    • ProfitsPercentChange
        dtype: float64; Label: Profits Percent Change
    • Assets_M
        dtype: int64; Label: Assets ($M)
    • CEO
        dtype: object; Label: CEO
    • Country
        dtype: category; Label: Country
    • HeadquartersCity
        dtype: object; Label: Headquarters City
    • HeadquartersState
        dtype: category; Label: Headquarters State
    • Website
        dtype: object; Label: Website
    • CompanyType
        dtype: category; Label: Company type
    • Footnote
        dtype: object; Label: Footnote
    • MarketCap_Updated_M
        dtype: float64; Label: Market value ($M)
    • Updated
        dtype: datetime64[ns]; Label: Updated Click to add a cell.
  3. w

    Fortune 500 Corporate Headquarters

    • data.wu.ac.at
    • hifld-geoplatform.opendata.arcgis.com
    Updated Jul 3, 2018
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department of Homeland Security (2018). Fortune 500 Corporate Headquarters [Dataset]. https://data.wu.ac.at/schema/data_gov/OGE5MjZkNmYtZjkxNC00Njc2LTg2ZDMtM2U4OWIxNDYwMWE0
    Explore at:
    Dataset updated
    Jul 3, 2018
    Dataset provided by
    Department of Homeland Security
    Description

    Large Corporate Headquarters in the United States This database is composed of 'an annual list of the 500 largest industrial corporations in the U.S., published by Fortune magazine. The corporations are ranked based on such metrics as revenues, profits, and market value', as defined by InvestorWords.com - http://www.investorwords.com/2056/Fortune_500.html The entities represented in this dataset are the companies' headquarters location only. This dataset does not include branches, divisions, annexes, or subdivisions of these company headquarters. There are no entities located in American Samoa, the Northern Mariana Islands, or the Virgin Islands included in this dataset. No emergency information was gathered by TGS for these entities. This includes the [EMERGTITLE], [EMERGPHONE], and [EMERGEXT] attributes. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g. the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 12/13/2006 and the newest record dates from 12/18/2006.

  4. Z

    Data set discussed in "Beyond Fortune 500: Women in a Global Network of...

    • data.niaid.nih.gov
    Updated May 27, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Gastner, Michael T. (2023). Data set discussed in "Beyond Fortune 500: Women in a Global Network of Directors" [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_3553441
    Explore at:
    Dataset updated
    May 27, 2023
    Dataset provided by
    Gastner, Michael T.
    Evtushenko, Anna
    License

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

    Description

    Bipartite graph of directors and companies. Data in GML format. Generated from information on the Financial Times web site (https://markets.ft.com/data/equities/results), retrieved on 17 September 2016.

    Vertex attributes:

    id: unique identifier

    type: "Person" or "Company"

    age: years of age for vertices representing a person, "NA" if unknown for a person or if vertex represents a company

    gender: "Male", "Female" or "NA" (unknown) if vertex represents a person, "NA" if vertex represents a company

    country: name of country or "NA" (unknown) if vertex represents a company, "NA" if vertex represents a person

    sector: segment of the economy in which a company operates. "NA" if vertex represents a person or if company's sector is unknown

    industry: specific business (i.e. subset of sector) in which a company operates. "NA" if vertex represents a person or if company's industry is unknown.

    employeesnum: number of company's employees. "NA" if vertex represents a person or if company's number of employees is unknown.

  5. Measuring innovation using Fortune 500 rankings (2006-2020)

    • figshare.com
    txt
    Updated Jun 6, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Richard Ferrers (2023). Measuring innovation using Fortune 500 rankings (2006-2020) [Dataset]. http://doi.org/10.6084/m9.figshare.870121.v11
    Explore at:
    txtAvailable download formats
    Dataset updated
    Jun 6, 2023
    Dataset provided by
    figshare
    Authors
    Richard Ferrers
    License

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

    Description

    This is a time-series extract from Fortune 500 (2006 to 2020) showing ranking of several companies over that period. Described in a blog post linked below. This is data to show a proxy of innovation measurement from changes in sales (which Fortune 500 measures) over time. This data could be used for Science Policy to indicate where in the economy innovation (in the form of rising sales) is taking place. Now updated for 2016 data. Now updated with 2018 Fortune 500 data (22.5.18). Updated graphic with 2020 Fortune 500 data.Facebook continues to make moves up the F500 in 2020.

  6. Percentage of female CEOs in Fortune 500 companies 1995-2014

    • statista.com
    Updated Aug 7, 2014
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2014). Percentage of female CEOs in Fortune 500 companies 1995-2014 [Dataset]. https://www.statista.com/statistics/319672/percentage-of-female-ceos-in-fortune-500-companies/
    Explore at:
    Dataset updated
    Aug 7, 2014
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1995 - 2014
    Area covered
    United States
    Description

    The statistic shows the percentage of female CEOs in Fortune 500 companies in the United States from 1995 to 2014. In 2000, about 0.4 percent of Fortune 500 CEOs were women.

    The ranking of the largest 100 companies globally based on market value can be accessed here.

  7. Targeted Email List | Global Database | 2 Billion+ Contacts

    • datacaptive.com
    Updated May 11, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    DataCaptive™ (2025). Targeted Email List | Global Database | 2 Billion+ Contacts [Dataset]. https://www.datacaptive.com/targeted-email-lists/
    Explore at:
    Dataset updated
    May 11, 2025
    Dataset provided by
    DataCaptive
    Authors
    DataCaptive™
    Area covered
    New Zealand, Finland, Canada, Mexico, Belgium, United States, Georgia, Kuwait, Ireland, Netherlands
    Description

    Discover unparalleled business opportunities with our Targeted Email List, featuring over 2 billion global contacts.

    Explore our global B2B contact and company database, providing essential data fields including Name, Website, Contact First Name, Contact Last Name, Job Title, Email Address, Phone Number, Revenue Size, Employee Size, Location, City, State, Country, Zip Code, and additional customizable data fields upon request. Access a comprehensive repository tailored to meet your specific business needs, ensuring you have access to accurate and detailed information for effective networking and targeted outreach.

  8. m

    List of ‘FORTUNE GLOBAL 500’ organizations (2015)

    • data.mendeley.com
    Updated Jun 5, 2017
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Hailing Chen (2017). List of ‘FORTUNE GLOBAL 500’ organizations (2015) [Dataset]. http://doi.org/10.17632/nk6tvbc6tt.1
    Explore at:
    Dataset updated
    Jun 5, 2017
    Authors
    Hailing Chen
    License

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

    Description

    This data is utilized for research on social media & social enterprise, and provide number of social media platform that is utilized by each organization.

  9. d

    Database on Ideology, Money in Politics, and Elections (DIME)

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 21, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Bonica, Adam (2023). Database on Ideology, Money in Politics, and Elections (DIME) [Dataset]. http://doi.org/10.7910/DVN/O5PX0B
    Explore at:
    Dataset updated
    Nov 21, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Bonica, Adam
    Time period covered
    Jan 1, 1979 - Jan 1, 2014
    Description

    Abstract: The Database on Ideology, Money in Politics, and Elections (DIME) is intended as a general resource for the study of campaign finance and ideology in American politics. The database was developed as part of the project on Ideology in the Political Marketplace, which is an on-going effort to perform a comprehensive ideological mapping of political elites, interest groups, and donors using the common-space CFscore scaling methodology (Bonica 2014). Constructing the database required a large-scale effort to compile, clean, and process data on contribution records, candidate characteristics, and election outcomes from various sources. The resulting database contains over 130 million political contributions made by individuals and organizations to local, state, and federal elections spanning a period from 1979 to 2014. A corresponding database of candidates and committees provides additional information on state and federal elections. The DIME+ data repository on congressional activity extends DIME to cover detailed data on legislative voting, lawmaking, and political rhetoric. (See http://dx.doi.org/10.7910/DVN/BO7WOW for details.) The DIME data is available for download as a standalone SQLite database. The SQLite database is stored on disk and can be accessed using a SQLite client or queried directly from R using the RSQLite package. SQLite is particularly well-suited for tasks that require searching through the database for specific individuals or contribution records. (Click here to download.) Overview: The database is intended to make data on campaign finance and elections (1) more centralized and accessible, (2) easier to work with, and (3) more versatile in terms of the types of questions that can be addressed. A list of the main value-added features of the database is below: Data processing: Names, addresses, and occupation and employer titles have been cleaned and standardized. Unique identifiers: Entity resolution techniques were used to assign unique identifiers for all individual and institutional donors included in the database. The contributor IDs make it possible to track giving by individuals across election cycles and levels of government. Geocoding: Each record has been geocoded and placed into congressional districts. The geocoding scheme relies on the contributor IDs to assign a complete set of consistent geo-coordinates to donors that report their full address in some records but not in others. This is accomplished by combining information on self-reported address across records. The geocoding scheme further takes into account donors with multiple addresses. Geocoding was performed using the Data Science Toolkit maintained by Pete Warden and hosted at http://www.datasciencetoolkit.org/. Shape files for congressional districts are from Census.gov (http://www.census.gov/rdo/data). Ideological measures: The common-space CFscores allow for direct distance comparisons of the ideal points of a wide range of political actors from state and federal politics spanning a 35 year period. In total, the database includes ideal point estimates for 70,871 candidates and 12,271 political committees as recipients and 14.7 million individuals and 1.7 million organizations as donors. Corresponding data on candidates, committees, and elections: The recipient database includes information on voting records, fundraising statistics, election outcomes, gender, and other candidate characteristics. All candidates are assigned unique identifiers that make it possible to track candidates if they campaign for different offices. The recipient IDs can also be used to match against the database of contribution records. The database also includes entries for PACs, super PACs, party committees, leadership PACs, 527s, state ballot campaigns, and other committees that engage in fundraising activities. Identifying sets of important political actors: Contribution records have been matched onto other publicly available databases of important political actors. Examples include: Fortune 500 directors and CEOs: (Data) (Paper) Federal court judges: (Data) (Paper} State supreme court justices: (Data) (Paper} Executives appointees to federal agencies: (Data) (Paper) Medical professionals: (Data) (Paper)

  10. m

    The Path to Becoming a Fortune 500 CIO

    • data.mendeley.com
    Updated Feb 14, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Degan Kettles (2025). The Path to Becoming a Fortune 500 CIO [Dataset]. http://doi.org/10.17632/phgywg4ghd.2
    Explore at:
    Dataset updated
    Feb 14, 2025
    Authors
    Degan Kettles
    License

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

    Description

    This study examines LinkedIn data from 400 Fortune 500 CIOs and 2,842 other C-level executives, supplemented by in-depth interviews with six current or former Fortune 500 CIOs. The dataset includes information on educational background, career progression timelines, and prior work experiences. The dataset provides valuable insights for aspiring CIOs, HR professionals, and researchers studying executive career paths in the technology sector.

  11. B2B Marketing Data | Global Marketing Leaders | Verified Profiles with...

    • datarade.ai
    Updated Oct 27, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Success.ai (2021). B2B Marketing Data | Global Marketing Leaders | Verified Profiles with Contact Info for CMOs & Marketers | Best Price Guaranteed [Dataset]. https://datarade.ai/data-products/b2b-marketing-data-global-marketing-leaders-verified-prof-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Oct 27, 2021
    Dataset provided by
    Area covered
    Micronesia (Federated States of), Central African Republic, Lesotho, Austria, Latvia, Singapore, Ukraine, Taiwan, Togo, Marshall Islands
    Description

    Success.ai’s B2B Marketing Data and Contact Data for Global Marketing Leaders empowers businesses to connect with chief marketing officers (CMOs), marketing strategists, and industry decision-makers worldwide. With access to over 170M verified profiles, including work emails and direct phone numbers, this dataset ensures your outreach efforts reach the right audience effectively.

    Our AI-powered platform continuously updates and validates contact data to maintain 99% accuracy, providing actionable insights for marketing campaigns, sales strategies, and recruitment initiatives. Whether you’re targeting CMOs in Fortune 500 companies or strategists in innovative startups, Success.ai delivers reliable data tailored to meet your business goals.

    Key Features of Success.ai’s Marketing Leader Contact Data - Comprehensive Coverage Across the Marketing Industry Access profiles for marketing leaders across diverse industries and regions:

    Chief Marketing Officers (CMOs): Decision-makers shaping global marketing strategies. Marketing Strategists: Experts driving innovative campaigns and business growth. Digital Marketing Heads: Leaders overseeing digital transformation initiatives. Brand Managers: Professionals managing brand identity and outreach efforts. Content and SEO Specialists: Key contributors to content strategy and visibility.

    • Verified Accuracy with Continuous Updates

    AI-Validated Accuracy: Industry-leading AI technology ensures every contact detail is verified. Real-Time Profile Updates: Data is continuously refreshed to reflect the most current information. Reliable Engagement: Minimized bounce rates for seamless communication with decision-makers.

    • Tailored Data Delivery Options Choose the delivery method that aligns with your operational requirements:

    API Integration: Seamlessly integrate contact data into your CRM or marketing platforms. Custom Flat Files: Receive datasets customized to your specifications, ready for immediate use.

    Why Choose Success.ai for Marketing Data?

    • Best Price Guarantee We provide the most competitive pricing in the industry, ensuring the best value for global, verified contact data.

    • Global Compliance and Ethical Practices Our data collection and processing adhere to strict compliance standards, including GDPR, CCPA, and other regional data regulations, ensuring ethical and secure usage.

    • Strategic Advantages for Your Business

      Precise Marketing Campaigns: Create highly targeted campaigns that resonate with marketing leaders. Effective Sales Outreach: Accelerate sales processes with direct access to CMOs and strategists. Recruitment Efficiency: Source top-tier marketing talent with verified contact data. Market Intelligence: Leverage enriched data insights to understand industry trends and optimize strategies. Partnership Development: Build and nurture relationships with influential marketing professionals.

    • Data Highlights 170M+ Verified Professional Profiles 50M Work Emails 700M Global Professional Profiles 70M Verified Company Profiles

    Key APIs for Enhanced Functionality

    • Enrichment API Keep your contact database updated with real-time enrichment capabilities, ensuring relevance for dynamic outreach efforts.

    • Lead Generation API Maximize your lead generation campaigns with accurate, verified data, including contact information for global marketing leaders. Our API supports up to 860,000 API calls per day, enabling robust scalability for your business.

    • Use Cases

    1. Targeted Marketing Campaigns Reach CMOs and marketing strategists with personalized campaigns designed to deliver measurable ROI.

    2. Sales Pipeline Acceleration Engage directly with decision-makers to shorten sales cycles and boost deal closure rates.

    3. Talent Recruitment Identify and recruit top-tier marketing talent to strengthen your team.

    4. Partnership Building Establish meaningful connections with global marketing leaders to foster collaboration.

    5. Strategic Planning Utilize detailed firmographic and demographic insights for data-driven decision-making.

    What Makes Success.ai Stand Out?

    • Unmatched Data Quality: AI-driven verification ensures 99% accuracy for all profiles. Comprehensive Reach: Covering marketing professionals across various industries and regions worldwide.
    • Flexible Integration Options: Customizable delivery formats to suit your business needs.
    • Ethical and Compliant Data: Fully aligned with global data protection regulations.

    Success.ai’s B2B Contact Data for Global Marketing Leaders is your ultimate solution for connecting with top-tier marketing professionals. From CMOs driving global strategies to strategists shaping impactful campaigns, our database ensures you reach the right audience to grow your business.

    No one beats us on price. Period.

  12. Biggest companies in the world by market value 2024

    • statista.com
    • ai-chatbox.pro
    Updated May 30, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Biggest companies in the world by market value 2024 [Dataset]. https://www.statista.com/statistics/263264/top-companies-in-the-world-by-market-capitalization/
    Explore at:
    Dataset updated
    May 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 17, 2024
    Area covered
    World
    Description

    With a market capitalization of 3.12 trillion U.S. dollars as of May 2024, Microsoft was the world’s largest company that year. Rounding out the top five were some of the world’s most recognizable brands: Apple, NVIDIA, Google’s parent company Alphabet, and Amazon. Saudi Aramco led the ranking of the world's most profitable companies in 2023, with a pre-tax income of nearly 250 billion U.S. dollars. How are market value and market capitalization determined? Market value and market capitalization are two terms frequently used – and confused - when discussing the profitability and viability of companies. Strictly speaking, market capitalization (or market cap) is the worth of a company based on the total value of all their shares; an important metric when determining the comparative value of companies for trading opportunities. Accordingly, many stock exchanges such as the New York or London Stock Exchange release market capitalization data on their listed companies. On the other hand, market value technically refers to what a company is worth in a much broader context. It is determined by multiple factors, including profitability, corporate debt, and the market environment as a whole. In this sense it aims to estimate the overall value of a company, with share price only being one element. Market value is therefore useful for determining whether a company’s shares are over- or undervalued, and in arriving at a price if the company is to be sold. Such valuations are generally made on a case-by-case basis though, and not regularly reported. For this reason, market capitalization is often reported as market value. What are the top companies in the world? The answer to this question depends on the metric used. Although the largest company by market capitalization, Microsoft's global revenue did not manage to crack the top 20 companies. Rather, American multinational retailer Walmart was ranked as the largest company in the world by revenue. Walmart also had the highest number of employees in the world.

  13. d

    Phone Number Data | APAC | 100M+ B2B Mobile Phone Numbers | 95%+ Accuracy

    • datarade.ai
    .json, .csv
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Forager.ai, Phone Number Data | APAC | 100M+ B2B Mobile Phone Numbers | 95%+ Accuracy [Dataset]. https://datarade.ai/data-products/apac-b2b-mobile-data-90m-95-accuracy-api-bi-weekly-up-forager-ai
    Explore at:
    .json, .csvAvailable download formats
    Dataset provided by
    Forager.ai
    Area covered
    Georgia, San Marino, Burkina Faso, Ghana, Libya, Belarus, Bhutan, Uruguay, El Salvador, Bahamas
    Description

    Global B2B Mobile Phone Number Database | 100M+ Verified Contacts | 95% Accuracy Forager.ai provides the world’s most reliable mobile phone number data for businesses that refuse to compromise on quality. With 100 million+ professionally verified mobile numbers refreshed every 3 weeks, our database ensures 95% accuracy – so your teams never waste time on dead-end leads.

    Why Our Data Wins ✅ Accuracy You Can Trust 95% of mobile numbers are verified against live carrier records and tied to current job roles. Say goodbye to “disconnected number” voicemails.

    ✅ Depth Beyond Digits Each contact includes 150+ data points:

    Direct mobile numbers

    Current job title, company, and department

    Full career history + education background

    Location data + LinkedIn profiles

    Company size, industry, and revenue

    ✅ Freshness Guaranteed Bi-weekly updates combat job-hopping and role changes – critical for sales teams targeting decision-makers.

    ✅ Ethically Sourced & Compliant First-party collected data with full GDPR/CCPA compliance.

    Who Uses This Data?

    Sales Teams: Cold-call C-suite prospects with verified mobile numbers.

    Marketers: Run hyper-personalized SMS/WhatsApp campaigns.

    Recruiters: Source passive candidates with up-to-date contact intel.

    Data Vendors: License premium datasets to enhance your product.

    Tech Platforms: Power your SaaS tools via API with enterprise-grade B2B data.

    Flexible Delivery, Instant Results

    API (REST): Real-time integration for CRMs, dialers, or marketing stacks

    CSV/JSON: Campaign-ready files.

    PostgreSQL: Custom databases for large-scale enrichment

    Compliance: Full audit trails + opt-out management

    Why Forager.ai? → Proven ROI: Clients see 62% higher connect rates vs. industry averages (request case studies). → No Guesswork: Test-drive free samples before committing. → Scalable Pricing: Pay per record, license datasets, or get unlimited API access.

    B2B Mobile Phone Data | Verified Contact Database | Sales Prospecting Lists | CRM Enrichment | Recruitment Phone Numbers | Marketing Automation | Phone Number Datasets | GDPR-Compliant Leads | Direct Dial Contacts | Decision-Maker Data

    Need Proof? Contact us to see why Fortune 500 companies and startups alike trust Forager.ai for mission-critical outreach.

  14. s

    Keyword Database & Analytics

    • searchlogistics.com
    Updated Apr 1, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Keyword Database & Analytics [Dataset]. https://www.searchlogistics.com/learn/statistics/semrush-statistics/
    Explore at:
    Dataset updated
    Apr 1, 2025
    License

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

    Description

    Here’s a breakdown of Semrush's keyword database growth since 2017.

  15. d

    Replication Data for: Avenues of Influence: On the Political Expenditures of...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 21, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Bonica, Adam (2023). Replication Data for: Avenues of Influence: On the Political Expenditures of Corporations and Their Directors and Executives [Dataset]. http://doi.org/10.7910/DVN/6R1HAS
    Explore at:
    Dataset updated
    Nov 21, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Bonica, Adam
    Description

    This archive contains data on the political giving patterns of board members and CEOs of Fortune 500 companies used in "Avenues of Influence: On the Political Expenditures of Corporations and Their Directors and Executives." Abstract: The literature on corporate political influence has primarily focused on expenditures made by corporations and their PACs but has largely ignored the political activities of the individuals who lead these firms. To better understand the role of corporate elites in political advocacy, I introduce a new database of campaign contributions made by corporate directors and executives of Fortune 500 firms. Donating to political campaigns is nearly universal among corporate elites. When compared to corporate PACs, corporate elites are more ideological, more willing to support non-incumbents, and less likely to target powerful legislators. The results also reveal substantial heterogeneity in the political preferences of directors both across and within firms. In addition to challenging widely held beliefs about the political leanings of corporate elites, the prevalence of bipartisan boardrooms has important implications for how the preferences of key decision-makers within a firm shape its political activities.

  16. d

    North America Data | USA, Canada | Decision Makers, Owner, Founder, CEO |...

    • datarade.ai
    Updated Aug 31, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Exellius Systems (2024). North America Data | USA, Canada | Decision Makers, Owner, Founder, CEO | 91M+ Contacts | 100% Work Verified Emails, Direct Dials | 16+ Attributes [Dataset]. https://datarade.ai/data-products/north-south-america-data-usa-canada-brazil-decision-m-exellius-systems
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Aug 31, 2024
    Dataset authored and provided by
    Exellius Systems
    Area covered
    Canada, Americas, United States
    Description

    Welcome to the North America Data: Your Gateway to Strategic Connections Across the Americas

    In today’s fast-evolving business landscape, having the right data at your fingertips is crucial for success. North America Data offers an unmatched resource designed to empower businesses by providing access to key decision-makers across the vast and diverse markets of North and South America. Our meticulously curated database serves as the cornerstone of your strategic outreach efforts, enabling you to connect with the right people in the right places at the right time.

    What Makes Our Data Unique?

    Depth and Precision
    Our database is more than just a collection of names and contact details—it’s a gateway to deep, actionable insights about the people who shape industries. We go beyond basic data points to offer a nuanced understanding of top executives, owners, founders, and influencers. Whether you're looking to connect with a CEO of a Fortune 500 company or a founder of a dynamic startup, our data provides the precision you need to identify and engage the most relevant decision-makers.

    Our Data Sourcing Excellence

    Reliability and Integrity
    Our data is sourced from a variety of authoritative channels, ensuring that every entry is both reliable and relevant. We draw from respected business directories, publicly available records, and proprietary research methodologies. Each piece of data undergoes a rigorous vetting process, meticulously checked for accuracy, to ensure that you can trust the integrity of the information you receive.

    Primary Use-Cases and Industry Verticals

    Versatility Across Sectors
    The North America Data is a versatile tool designed to meet the needs of a wide range of industries. Whether you're in finance, manufacturing, technology, healthcare, retail, hospitality, energy, transportation, or any other sector, our database provides the critical insights necessary to drive your business forward. Use our data to:

    • Expand Market Presence: Identify and connect with key players in new markets.
    • Forge Strategic Partnerships: Reach out to potential collaborators and investors.
    • Conduct Market Research: Gain a deeper understanding of industry trends and dynamics.

      Seamless Integration with Broader Data Solutions

    Comprehensive Business Intelligence
    Our North America Data is not an isolated resource; it’s a vital component of our comprehensive business intelligence suite. When combined with our global datasets, it provides a holistic view of the global business landscape. This integrated approach enables businesses to make well-informed decisions, tapping into insights that span across continents and sectors.

    Geographical Coverage Across the Americas

    Pan-American Reach
    Our database covers the entirety of North and South America, offering a robust range of contacts across numerous countries, including but not limited to:

    • United States
    • Canada
    • Mexico
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Venezuela
    • And many more

      Extensive Industry Coverage

    Tailored to Your Sector
    We cater to a vast array of industries, ensuring that no matter your focus, our database has the coverage you need. Key industries include:

    • Finance: Access to high-level contacts in banking, investment, and financial services.
    • Manufacturing: Connect with decision-makers in production, logistics, and supply chain management.
    • Technology: Engage with leaders in software, hardware, and IT services.
    • Healthcare: Reach out to executives in hospitals, pharmaceuticals, and biotech.
    • Retail: Identify key players in e-commerce, brick-and-mortar stores, and consumer goods.
    • Hospitality: Connect with industry leaders in hotels, travel, and leisure.
    • Energy: Tap into contacts within oil, gas, renewable energy, and utilities.
    • Transportation: Engage with decision-makers in logistics, shipping, and infrastructure.

      Comprehensive Employee Size and Revenue Data

    Insights Across Business Sizes
    Our database doesn’t just provide contact information—it also includes detailed data on employee size and revenue. Whether you’re targeting small startups, mid-sized enterprises, or large multinational corporations, our database has the depth to accommodate your needs. We offer insights into:

    • Employee Size: From small businesses with 1-10 employees to large enterprises with 10,000+ employees.
    • Revenue Size: Covering companies ranging from early-stage startups to global giants in the Fortune 500.

      Empower Your Business with Unmatched Data Access

    Unlock Opportunities Across the Americas
    With the North America Data, you gain access to a powerful resource designed to unlock endless opportunities for growth and success. Whether you’re looking to break into new markets, establish strong business relationships, or enhance your market intelligence, our database equips you with the tools you need to excel.

    Explore the North America Data tod...

  17. 57M+ Business Email Lists | SMBs & Enterprises Leads [2025]

    • datacaptive.com
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    DataCaptive™, 57M+ Business Email Lists | SMBs & Enterprises Leads [2025] [Dataset]. https://www.datacaptive.com/business-email-list/
    Explore at:
    Dataset provided by
    DataCaptive
    Authors
    DataCaptive™
    Area covered
    Norway, Greece, New Zealand, Switzerland, Poland, Jordan, Spain, Netherlands, Ireland, United Kingdom
    Description

    Target SMBs & enterprise leaders, CEOs, owners & execs from startups to Fortune 500 companies. Download FREE sample business email list today!

  18. Percentage of women among Fortune 500 CMOs in the U.S. 2021-2024

    • statista.com
    • ai-chatbox.pro
    Updated Apr 4, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Percentage of women among Fortune 500 CMOs in the U.S. 2021-2024 [Dataset]. https://www.statista.com/statistics/1285809/share-women-cmo-us/
    Explore at:
    Dataset updated
    Apr 4, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2024, approximately 53 percent of Fortune 500 companies' chief marketing officers (CMOs) in the United States were women. A year earlier, the share stood at 50 percent. Meanwhile, the percentage of underrepresented ethnic groups among Fortune 500 CMOs in the U.S. remained the same.

  19. d

    Company Data | Global Coverage | 65M+ Company profiles | Bi-weekly updates

    • datarade.ai
    .json, .csv
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Forager.ai, Company Data | Global Coverage | 65M+ Company profiles | Bi-weekly updates [Dataset]. https://datarade.ai/data-products/b2b-company-data-worldwide-61m-records-verified-updated-forager-ai-351c
    Explore at:
    .json, .csvAvailable download formats
    Dataset provided by
    Forager.ai
    Area covered
    United States Minor Outlying Islands, Iran (Islamic Republic of), Falkland Islands (Malvinas), Madagascar, Kyrgyzstan, United States of America, Guatemala, Faroe Islands, Sint Maarten (Dutch part), Tunisia
    Description

    Global B2B Company Database | 65M+ Verified Firms | Firmographics Forget stale corporate directories – Forager.ai delivers living, breathing company intelligence trusted by VCs, Fortune 500 teams, and SaaS leaders. Our 65 million+ AI-validated company profiles are refreshed every 14 days to track leadership changes, tech migrations, and growth signals competitors miss.

    Why This Outperforms Generic Firmographics ✅ AI That Works Like Your Best Analyst Cross-references 12+ sources to: ✔ Flag companies hiring sales teams → Ready to buy ✔ Detect tech stack changes → Migration opportunities ✔ Identify layoffs/expansions → Timely outreach windows

    ✅ Freshness That Matters We update 100% of records every 2-3 weeks – critical for tracking:

    Funding round and revenue.

    Company job posts

    ✅ Ethical & Audit-Ready Full GDPR/CCPA compliance with:

    Usage analytics dashboard

    Your Secret Weapon for: 🔸 Sales Teams: → Identify high-growth targets 83% faster (employee growth + tech stack filters) → Prioritize accounts with "hiring spree" or "new funding" tags

    🔸 Investors: → Track 18K+ private companies with revenue/employee alerts → Portfolio monitoring with 92% prediction accuracy on revenue shifts

    🔸 Marketers: → ABM campaigns powered by technographics (Slack → Teams migrators) → Event targeting using travel patterns (HQ → conference city matches)

    🔸 Data Teams: → Enrich Snowflake/Redshift warehouses via API → Build custom models with 150+ firmographic/technographic fields

    Core Data Points ✔ Financial Health: Revenue ranges, funding history, growth rate estimates ✔ Tech Stack: CRM, cloud platforms, marketing tools, Web technologies used. ✔ People Moves: C-suite, Employees headcount ✔ Expansion Signals: New offices, job postings.

    Enterprise-Grade Delivery

    API: Credits system to find company using any field in schema; returns name, domain, industry, headcount, location, LinkedIn etc.

    Cloud Sync: Auto-update Snowflake/Redshift/BigQuery

    CRM Push: Direct to Salesforce/HubSpot/Pipedrive

    Flat Files: CSV/JSON

    Why Clients Never Go Back to Legacy Providers → 6-Month ROI Guarantee – We’ll beat your current vendor or extend your plan → Free Data Audit – Upload your CRM list → We’ll show gaps/opportunities → Live Training – Our analysts teach you to mine hidden insights

    Keywords (Naturally Integrated): Global Company Data | Firmographic Database | B2B Technographic data | Private Company Intelligence | CRM Enrichment API | Sales Lead Database | VC Due Diligence Data | AI-Validated Firmographics | Market Expansion Signals | Competitor Benchmarking

  20. United HealthCare Stock data

    • kaggle.com
    Updated Mar 12, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kalilur Rahman (2025). United HealthCare Stock data [Dataset]. https://www.kaggle.com/datasets/kalilurrahman/united-healthcare-stock-data/versions/159
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Kalilur Rahman
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    https://upload.wikimedia.org/wikipedia/commons/thumb/f/f3/UnitedHealth_Group_logo.svg/330px-UnitedHealth_Group_logo.svg.png" alt=""> https://www.pngkit.com/png/full/944-9444695_united-healthcare-graphic-design.png" alt=""> UHG is a very big market cap player.

    UnitedHealth Group Incorporated is an American multinational managed healthcare and insurance company based in Minnetonka, Minnesota. It offers health care products and insurance services. UnitedHealth Group is the world's eighth-largest company by revenue and second-largest healthcare company behind CVS Health by revenue, and the largest insurance company by net premiums. UnitedHealthcare revenues comprise 80% of the Group's overall revenue

    The company is ranked 8th on the 2021 Fortune Global 500. UnitedHealth Group has a market capitalization of $400.7 billion as of March 31, 2021.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Aurielle Perlmann (2022). Fortune 500 - 2017 [Dataset]. https://data.world/aurielle/fortune-500-2017
Organization logo

Fortune 500 - 2017

Explore at:
45 scholarly articles cite this dataset (View in Google Scholar)
zip, csvAvailable download formats
Dataset updated
Dec 14, 2022
Dataset provided by
data.world, Inc.
Authors
Aurielle Perlmann
Description

aurielle is using data.world to share Fortune 500 - 2017 data

Search
Clear search
Close search
Google apps
Main menu