100+ datasets found
  1. d

    Business establishments location and industry classification

    • data.gov.au
    • researchdata.edu.au
    • +2more
    csv, geojson, json +1
    Updated Jan 11, 2021
    + more versions
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    data.melbourne.vic.gov.au (2021). Business establishments location and industry classification [Dataset]. https://data.gov.au/dataset/ds-melbourne-business-establishments-with-address-and-industry-classification
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    csv, json, shp, geojsonAvailable download formats
    Dataset updated
    Jan 11, 2021
    Dataset provided by
    data.melbourne.vic.gov.au
    Description

    Data collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data covers the period 2002-2023. It show business establishments with their business address, …Show full descriptionData collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data covers the period 2002-2023. It show business establishments with their business address, industry (ANZSIC4) classification, location and CLUE block and small area allocation. A business establishment is defined as a • Commercial occupant in a building • Separate land use • Any permanent presence of economic activity in accordance with standard Industry classification (ANZSIC). Hence, if one organisation has its presence in several buildings in the CLUE area, each time it will be counted as a separate establishment. Consequently, the count of establishments presented in CLUE represents the number of locations, rather than 'enterprises'. For more information about CLUE see http://www.melbourne.vic.gov.au/clue For more information about the ANZSIC industry classification system see http://www.abs.gov.au/ausstats/abs@.nsf/mf/1292.0

  2. Time Series International Trade: Monthly U.S. Imports by North American...

    • datasets.ai
    • catalog.data.gov
    2
    Updated Sep 7, 2024
    + more versions
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    Department of Commerce (2024). Time Series International Trade: Monthly U.S. Imports by North American Industry Classification System (NAICS) Code [Dataset]. https://datasets.ai/datasets/time-series-international-trade-monthly-u-s-imports-by-north-american-industry-classificat
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    2Available download formats
    Dataset updated
    Sep 7, 2024
    Dataset provided by
    United States Department of Commercehttp://www.commerce.gov/
    Authors
    Department of Commerce
    Area covered
    United States
    Description

    The Census data API provides access to the most comprehensive set of data on current month and cumulative year-to-date imports using the North American Industry Classification System (NAICS). The NAICS endpoint in the Census data API also provides value, shipping weight, and method of transportation totals at the district level for all U.S. trading partners. The Census data API will help users research new markets for their products, establish pricing structures for potential export markets, and conduct economic planning. If you have any questions regarding U.S. international trade data, please call us at 1(800)549-0595 option #4 or email us at eid.international.trade.data@census.gov.

  3. a

    Data from: Business Establishments

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • data.peelregion.ca
    Updated Dec 31, 2007
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    Regional Municipality of Peel (2007). Business Establishments [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/RegionofPeel::business-establishments/about
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    Dataset updated
    Dec 31, 2007
    Dataset authored and provided by
    Regional Municipality of Peel
    License

    https://www.statcan.gc.ca/eng/reference/licencehttps://www.statcan.gc.ca/eng/reference/licence

    Area covered
    Description

    This table contains data from the December release of Canadian Business Counts for 2007 until the latest complete year. The data includes the year, 2-digit North American Industry Classification System (NAICS) code, and a count of the number of businesses by number of employees. The table data shows the number of businesses categorized by the number of employees they have. Please ensure you read the notes provided below, as there is very important information on classification and comparability. NotesStatistics Canada advises users not to use these data as a time series. Further, the counts may reflect some of the business openings and closures caused by the COVID-19 pandemic, although they will not be fully represented as the evolving resumption or permanent closure of businesses may not yet be fully processed and confirmed by Statistics Canada's Business Register (The Daily — Canadian business counts, December 2021 (statcan.gc.ca)).Changes in methodology or in business industrial classification strategies used by Statistics Canada's Business Register can create increases or decreases in the number of active businesses reported in the data on Canadian business patterns. As a result, these data do not represent changes in the business population over time. Statistics Canada recommends users not to use these data as a time series. Beginning in December 2014, there were several important changes that were made:

    The data appear in two separate series, one covering locations with employees, the other covering locations without employees. The second series corresponds to locations previously coded to the employment category called "indeterminate." A new North American Industrial Classification System (NAICS) category has been added to include locations that have not yet received a NAICS code: unclassified. It represents an additional 78,718 locations with employees and 313,107 locations without employees. The second series, locations without employees, also includes locations that were not previously included in tables but that meet the criteria used to define the Business Register coverage. The impact of the change will be the inclusion of approximately 600,000 additional locations.

    Before 2014, the following notes apply:

    The establishments in the "Indeterminate" category do not maintain an employee payroll, but may have a workforce which consists of contracted workers, family members or business owners. However, the Business Register does not have this information available, and has therefore assigned the establishments to an "Indeterminate" category. This category also includes employers who did not have employees in the last 12 months. Please note that the employment size ranges are based on data derived from payroll remittances. As such, it should be viewed solely as a business stratification variable. Its primary purpose is to improve the efficiency of samples selected to conduct statistical surveys. It should not be used in any manner to compile industry employment estimates. Employment, grouped in employment size ranges, is more often than not an estimation of the annual maximum number of employees. For example, a measure of "10 employees" could represent "10 full-time employees", "20 part-time employees" or any other combination.For more information refer to Statistics Canada's Definitions and Concepts used in Business Register.

  4. d

    B2B Contact Data Company Records - 18M+ US Business Data Records - Employee...

    • datarade.ai
    Updated Jun 14, 2025
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    Giant Partners (2025). B2B Contact Data Company Records - 18M+ US Business Data Records - Employee Profiles & Contact Info [Dataset]. https://datarade.ai/data-products/b2b-contact-data-company-records-18m-us-business-data-reco-giant-partners
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    Dataset updated
    Jun 14, 2025
    Dataset authored and provided by
    Giant Partners
    Area covered
    United States of America
    Description

    Premium B2B Marketing Database - 18+ Million Company Records

    Accelerate your B2B sales and marketing success with our comprehensive business database featuring over 18 million verified company records and 70 million employee profiles. Our 20+ year data expertise delivers superior quality and coverage compared to competitors.

    Core Database Statistics

    Company Records: 18,243,524 (verified businesses)

    Employee Records: 70,420,010 (professional profiles)

    Business Email Addresses: 38,731,006 (verified and deliverable)

    Phone Numbers: 9,728,410 (direct business lines)

    Geographic Coverage: Complete US business landscape

    Industry Classification: Full SIC code taxonomy

    Advanced Targeting Categories

    Geographic Targeting: Target businesses by precise location parameters including nationwide campaigns, state-level focus, Metropolitan Service Areas (MSA), zip code radius, city and county targeting, and carrier route precision for local market penetration.

    Business Profile Segmentation: Segment companies by annual revenue (sales volume), employee count (startup to enterprise), year founded (established vs. emerging), business type (small business, corporation, public company), facility ownership status, stock exchange listings (NYSE, NASDAQ, ASE), and franchise operations.

    Industry Classification (SIC Codes): Leverage Standard Industrial Classification codes for precision targeting across 2-digit (broad categories), 4-digit (sub-industries), 6-digit (niche markets), and 8-digit (hyper-specific) classifications covering all major industries including Manufacturing, Healthcare, Technology, Financial Services, Professional Services, and more.

    Employee & Decision Maker Targeting: Identify key decision makers by job title (C-level, VP, Director, Manager), department focus (IT, Marketing, Finance, Operations), purchasing authority levels, seniority positions, and functional roles across technical, administrative, and strategic positions.

    Multi-Channel Campaign Applications

    Deploy across all major B2B marketing channels:

    Email Marketing: Direct outreach to verified business email addresses

    LinkedIn Advertising: Professional network targeting with job title precision

    Social Media: Facebook, Instagram, and Twitter/X B2B campaigns

    Search Advertising: Google, BING and YouTube business targeting

    Direct Mail: Physical address campaigns for high-value prospects

    Telemarketing: Direct phone outreach to decision makers

    Account-Based Marketing: Multi-touch ABM campaign coordination

    Data Quality & Sources

    Our business database aggregates from multiple verified sources:

    Business registration and licensing records

    Professional association memberships and directories

    Industry publications and trade organizations

    Conference and trade show participation data

    Online business profiles and corporate websites

    Financial reporting and SEC filing information

    Employment databases and HR records

    Technical Delivery & Integration

    File Formats: CSV, Excel, JSON, XML formats available

    Delivery Methods: Secure FTP, API integration, direct download portals

    Integration Options: CRM systems, marketing automation platforms, ad platforms

    Custom Selections: 1,000+ selectable business and employee attributes

    Update Frequency: Monthly data refreshes with real-time validation

    Minimum Orders: Flexible based on targeting complexity and campaign size

    Account-Based Marketing (ABM) Excellence

    Specifically designed for sophisticated ABM strategies:

    Target Account Identification: Find companies matching ideal customer profiles

    Decision Maker Mapping: Multiple contacts within target accounts

    Account Prioritization: Focus on high-revenue, high-employee companies

    Personalized Outreach: Industry and company-specific messaging

    Multi-Touch Coordination: Synchronized campaigns across channels

    Unique Value Propositions

    20+ Year Data Heritage: Established industry expertise and proven track record

    Superior Data Coverage: More extensive and accurate than competitors

    Real-Time Validation: Continuous data refreshing and quality assurance

    Advanced Segmentation: Combine multiple targeting criteria for precision

    Compliance Management: Built-in suppression lists and opt-out handling

    Technical Flexibility: API access and custom integration support

    Ideal Customer Profiles

    Technology Companies: Software, SaaS, hardware, and IT services

    Professional Services: Consulting, legal, accounting, and advisory firms

    Financial Services: Banks, insurance, investment, and fintech companies

    Healthcare Organizations: Medical devices, pharmaceuticals, and healthcare IT

    Manufacturing Companies: Industrial equipment, automotive, and consumer goods

    Marketing Agencies: Digital agencies serving B2B clients

    Sales Organizations: Inside sales, field sales, and business development teams

    Performance Optimization Features

    Lookalike ...

  5. Broad Industry Group (Standard Industrial Classification) – Business...

    • cy.ons.gov.uk
    • ons.gov.uk
    xlsx
    Updated Nov 4, 2024
    + more versions
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    Office for National Statistics (2024). Broad Industry Group (Standard Industrial Classification) – Business Register and Employment Survey (BRES): Table 1 [Dataset]. https://cy.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/datasets/broadindustrygroupsicbusinessregisterandemploymentsurveybrestable1
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    xlsxAvailable download formats
    Dataset updated
    Nov 4, 2024
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Annual employee and employment estimates for Great Britain and UK split by broad industry group Standard Industrial Classification: SIC 2007. Results given by full-time or part-time and public or private splits.

  6. Business Census/Enterprise Statistics: Enterprises

    • data.europa.eu
    csv, esri rest, html +3
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    Ufficio federale di statistica, Business Census/Enterprise Statistics: Enterprises [Dataset]. https://data.europa.eu/data/datasets/ecc82a85-9ecb-4f14-873d-bd07d8468bad-bundesamt-fur-statistik-bfs?locale=en
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    unknown, esri rest, html, wmts, wms, csvAvailable download formats
    Dataset provided by
    Federal Statistical Officehttp://www.bfs.admin.ch/
    Authors
    Ufficio federale di statistica
    License

    http://dcat-ap.ch/vocabulary/licenses/terms_by_askhttp://dcat-ap.ch/vocabulary/licenses/terms_by_ask

    Description

    Since 1995, coordinates have been allocated to all establishments recorded in federal business censuses. After each census, detailed information of businesses locations and full-time and part-time employment in all economic sectors according to NOGA (General Classification of Economic Activities) are aggregated in hectares and published as geodata.Since 2011 the business census is replaced by the structural business statistics (STATENT), an annual full survey of business and economic information taken from the registers of the OASI administration (Swiss social insurance system). STATENT provides important information about the structure of the Swiss economy (e.g. number of enterprises, number of workforce), delivering a general overview over the economic landscape of Switzerland.

  7. G

    Innovation, selected service industries, percentage of full-time employees...

    • open.canada.ca
    • www150.statcan.gc.ca
    csv, html, xml
    Updated Jan 17, 2023
    + more versions
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    Statistics Canada (2023). Innovation, selected service industries, percentage of full-time employees who were university graduates [Dataset]. https://open.canada.ca/data/en/dataset/89b3816e-8305-4617-965c-b91df774ab83
    Explore at:
    html, csv, xmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canada
    License

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

    Description

    Innovation, selected service industries, percentage of full-time employees who were university graduates, by type of business units, percentage range of full-time employees and North American Industry Classification System (NAICS) for Canada, provinces and territories in 2003. (Terminated)

  8. d

    Canaria | Firmographic Data | USA | +25M Unique Companies & 2 Years...

    • datarade.ai
    Updated Jul 9, 2024
    + more versions
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    Canaria Inc. (2024). Canaria | Firmographic Data | USA | +25M Unique Companies & 2 Years Historical Firmographic Data | Industry classification with NAICS - SOC - SIC [Dataset]. https://datarade.ai/data-products/canaria-firmographic-data-usa-300000-unique-companies-canaria-inc
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    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jul 9, 2024
    Dataset authored and provided by
    Canaria Inc.
    Area covered
    United States
    Description

    Detailed Data Dictionary: https://docs.google.com/spreadsheets/d/1Rvsb53lfYA00A2PJU22lSR44EBgtAThdeDrdhl_NGJk/edit?gid=1071313126gid=1071313126

    Advanced Processing, Superior Insights

    Utilizing state-of-the-art AI and large language models (LLMs) validated by human experts, we are dedicated to delivering high-quality, actionable data through innovative technology. Apart from the models included in our standard data offerings, we have developed additional models to provide tailored results to your needs, such as a sentiment analysis model that analyzes text data to gauge sentiment, helping businesses understand public perception and employee feedback, anomaly detection models, and LLM-based summarization models that condense large chunks of text for you.

    Our Models:

    • Deduplication Model: Our model first removes exact duplicate records, then uses advanced AI to identify and eliminate near-duplicate job postings across different URLs, achieving approximately a 60% deduplication rate.

    • Title Taxonomy Model: With over 20 million unique job titles in our 500M+ job postings database, analysis can be challenging. Our AI models categorize each job posting into one of 50,000 standardized job titles from our internal normalized title taxonomy, simplifying data analysis.

    • Skill Taxonomy Model: Our in-house AI model identifies key entities in job postings, including hard skills, soft skills, certifications, and qualifications. Unlike keyword-based approaches, our model not only finds relevant keywords but also excludes irrelevant ones, ensuring precise data (e.g., "Hepatitis B" is skill for nursing jobs but not for accounting jobs).

    • Job Category Model: Our AI models analyze job descriptions, entities, predicted salary, location, industry, and job title to determine the seniority level of a job, standardizing levels across different companies. Another model identifies if a job is remote, onsite, or hybrid, accounting for discrepancies between job classifications and descriptions (e.g., a job classified as onsite but open to remote).

    • Salary Estimation Model: Using company salary history, industry ranges, location, seniority, and public government data, our models predict the salary range for job postings.

    • Government Classification Models: We developed models to classify job postings into Standard Occupation Codes (SOC) by the BLS and to categorize companies into industries based on their job posting information.

    Canaria's Firmographic Data is unparalleled in its depth, accuracy, and comprehensiveness. Our firmographic data product offers detailed information on companies, including names, URLs, addresses, industries, revenues, employee counts, and more. We pride ourselves on the precision of our geographical firmographic data, including latitude, longitude, city, state, and zipcode information, which enables accurate location-based analysis.

    Our firmographic data is updated regularly, ensuring that users always have access to the most current and reliable information. This commitment to accuracy and relevance sets Canaria's Firmographic Data apart from other firmographic data products on the market. Furthermore, our extensive coverage spans a wide range of industries and countries, providing users with a global perspective that is essential for thorough market analysis and strategic decision-making.

    Canaria's Firmographic Data is sourced from a combination of public records, proprietary databases, industry reports, and direct submissions from companies. This multi-source approach ensures a high level of accuracy and completeness. We employ rigorous validation processes, including automated checks and manual reviews, to further enhance firmographic data quality. Our sourcing strategy not only ensures comprehensive coverage but also maintains the integrity and reliability of the firmographic data.

    Market Analysis:

    • Identify Emerging Trends: Use our firmographic data to uncover trends within specific industries and geographical regions. • Assess Market Dynamics: Gain a deep understanding of market conditions and competitive landscapes.

    Competitive Benchmarking:

    • Compare Against Industry Peers: Benchmark your company's performance metrics against those of industry leaders using our detailed firmographic data. • Gain Competitive Insights: Identify strengths and weaknesses relative to competitors.

    Targeted Marketing:

    • Segment and Target Clients: Utilize our firmographic data to create precise segments and target potential clients effectively. • Personalize Marketing Campaigns: Tailor your marketing strategies based on detailed firmographic profiles.

    Geographical Analysis:

    • Develop Location-Based Strategies: Leverage geographical firmographic data to identify optimal regions for business expansion and strategy development. • Analyze Regional Industry Distribution: Understand the distribution of industries across different regions.

    Academic R...

  9. Region by broad industry group (Standard Industrial Classification) –...

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Nov 4, 2024
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    Office for National Statistics (2024). Region by broad industry group (Standard Industrial Classification) – Business Register and Employment Survey (BRES): Table 4 [Dataset]. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/datasets/regionbybroadindustrygroupsicbusinessregisterandemploymentsurveybrestable4
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    xlsxAvailable download formats
    Dataset updated
    Nov 4, 2024
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Annual employee and employment estimates for the UK split by region and broad industry group Standard Industrial Classification: SIC 2007. Results given by full-time or part-time and public or private splits.

  10. Enterprise Survey 2009 - Czech Republic

    • dev.ihsn.org
    • catalog.ihsn.org
    • +2more
    Updated Apr 25, 2019
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    European Bank for Reconstruction and Development (2019). Enterprise Survey 2009 - Czech Republic [Dataset]. https://dev.ihsn.org/nada/catalog/study/CZE_2009_ES_v01_M_WB
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    Dataset updated
    Apr 25, 2019
    Dataset provided by
    World Bankhttp://worldbank.org/
    European Bank for Reconstruction and Development
    Time period covered
    2008 - 2009
    Area covered
    Czechia
    Description

    Abstract

    The objective of the survey is to obtain feedback from enterprises in client countries on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

    The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.

    Geographic coverage

    National

    Analysis unit

    The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

    Universe

    The manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with International Standard Industrial Classification of All Economic Activities (ISIC) codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample for Azerbaijan was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and oblast (region).

    Industry stratification was designed in the way that follows: the universe was stratified into 23 manufacturing industries, 2 services industries -retail and IT-, and one residual sector. Each sector had a target of 90 interviews.

    Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

    Regional stratification was defined in eight regions. These regions are Praha, Stredni Cechy, Jihozapad, Severozapad, Severovychod, Jihovychod, Stredni Morava, and Moravskoslezsko.

    Given the stratified design, sample frames containing a complete and updated list of establishments for the selected regions were required. Great efforts were made to obtain the best source for these listings. However, the quality of the sample frames was not optimal and, therefore, some adjustments were needed to correct for the presence of ineligible units. These adjustments are reflected in the weights computation.

    For most countries covered in BEEPS IV, two sample frames were used. The first was supplied by the World Bank and consisted of enterprises interviewed in BEEPS 2005. The World Bank required that attempts should be made to re-interview establishments responding to the BEEPS 2005 survey where they were within the selected geographical regions and met eligibility criteria. That sample is referred to as the Panel. The second frame for the Czech Republic was an official database known as Albertina data [Creditinfo Czech Republic], which is obtained from the complete Business Register [RES] of the Czech Statistical Office. An extract from that frame was sent to the TNS statistical team in London to select the establishments for interview.

    The quality of the frame was assessed at the onset of the project. The frame proved to be useful though it showed positive rates of non-eligibility, repetition, non-existent units, etc. These problems are typical of establishment surveys, but given the impact these inaccuracies may have on the results, adjustments were needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of contacts to complete the survey was 28% (572 out of 2041 establishments).

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The current survey instruments are available: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72] - Screener Questionnaire.

    The “Core Questionnaire” is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments- the “Core Questionnaire + Manufacturing Module” and the “Core Questionnaire + Retail Module.” The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

    The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

    Cleaning operations

    Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

    Response rate

    Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in the document "Description of Czech Republic Implementation 2009.pdf"

  11. Occupant Classification System (OCS) Market By sensor (seat belt tension...

    • zionmarketresearch.com
    pdf
    Updated Jun 14, 2025
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    Zion Market Research (2025). Occupant Classification System (OCS) Market By sensor (seat belt tension sensor and pressure sensor), By component (sensors and airbag control units), By terms (mid-size, economy, and luxury) And By Region: - Global And Regional Industry Overview, Market Intelligence, Comprehensive Analysis, Historical Data, And Forecasts, 2024-2032 [Dataset]. https://www.zionmarketresearch.com/report/occupant-classification-system-market
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    pdfAvailable download formats
    Dataset updated
    Jun 14, 2025
    Dataset provided by
    Authors
    Zion Market Research
    License

    https://www.zionmarketresearch.com/privacy-policyhttps://www.zionmarketresearch.com/privacy-policy

    Time period covered
    2022 - 2030
    Area covered
    Global
    Description

    Occupant Classification System (OCS) Market valued at $2,805.10 Mn in 2023, and is projected to reach $USD 5,023.62 Mn by 2032, at a CAGR of 6.65%.

  12. d

    Manufacturing Industry (ISIC, Rev.3.1) Research and Development Manpower...

    • data.gov.tw
    csv
    Updated May 20, 2025
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    National Science and Technology Council (2025). Manufacturing Industry (ISIC, Rev.3.1) Research and Development Manpower Full-time Equivalent - Classified by Technological Intensity [Dataset]. https://data.gov.tw/en/datasets/40197
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    csvAvailable download formats
    Dataset updated
    May 20, 2025
    Dataset authored and provided by
    National Science and Technology Council
    License

    https://data.gov.tw/licensehttps://data.gov.tw/license

    Description
    1. In order to understand and grasp the development of science and technology in our country, and to establish scientific and technological indicators, as well as to objectively compare with other countries as a reference for the country to formulate science and technology development policies, the National Science and Technology Commission conducts the "National R&D Status Survey" regularly every year. This dataset is one of the statistical results of the "National R&D Status Survey".2. The OECD defines technology-intensive industries based on the International Standard Industrial Classification (Version 3.1).3. Full-time Equivalent (FTE) refers to the number of people engaged in a certain R&D work, converted to the number of people working full-time in that work. For example, if a researcher spends half of the working time on teaching and the other half on R&D in a year, then this researcher is equivalent to 0.5 "full-time equivalent" (or 0.5 person-years); if working full-time (calculated for 250 working days per year) on research, then it is equivalent to 1 "full-time equivalent". Source: Frascati Manual (OECD)4. "..." means no value.5. "0" means less than one unit.
  13. B

    Business Integrated Database, 1995 [Canada]

    • borealisdata.ca
    • search.dataone.org
    Updated Feb 21, 2024
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    Strategis Industry Canada (2024). Business Integrated Database, 1995 [Canada] [Dataset]. http://doi.org/10.5683/SP3/CWHUMB
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 21, 2024
    Dataset provided by
    Borealis
    Authors
    Strategis Industry Canada
    License

    https://borealisdata.ca/api/datasets/:persistentId/versions/3.1/customlicense?persistentId=doi:10.5683/SP3/CWHUMBhttps://borealisdata.ca/api/datasets/:persistentId/versions/3.1/customlicense?persistentId=doi:10.5683/SP3/CWHUMB

    Time period covered
    1995
    Area covered
    Canada
    Description

    The Business Integrated Database (BID) is not a survey, it is a joint Industry Canada and Statistics Canada compendium of statistical information. The database is organized by Standard Industrial Classification for Establishments (SIC-E) and only has four elements: the year, the SIC-E (four digit level), the Herfindahl Index (HI) at the SCG 4 digit level, and the HI at the SCG 6 digit level. The reference year for this file is 1995.

  14. Employment Trends

    • kaggle.com
    Updated Nov 29, 2024
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    Noey Ignacio (2024). Employment Trends [Dataset]. https://www.kaggle.com/datasets/noeyislearning/employment-trends
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 29, 2024
    Dataset provided by
    Kaggle
    Authors
    Noey Ignacio
    License

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

    Description

    This dataset provides a comprehensive overview of employment trends in Canada. The data is sourced from the Survey of Employment, Payrolls and Hours (SEPH), offering a detailed breakdown of employment levels across various industrial sectors. The dataset is structured to include key metrics such as geographical location, industry classification, and employment estimates, providing a robust foundation for analyzing employment dynamics within the country.

    Key Features

    • Employment Metrics: The dataset includes employment estimates for all employees, providing a complete picture of workforce dynamics across different industries.
    • Industrial Classification: Data is categorized by the North American Industry Classification System (NAICS), offering insights into employment trends within specific sectors such as industrial aggregate, goods producing industries, and more.
    • Geographical Focus: Data is specific to Canada, providing insights into national employment trends and patterns.
    • Unit of Measurement: Information is presented in units of persons, allowing for straightforward analysis and comparison.
    • Temporal Precision: The data is time-stamped for January 2001, ensuring relevance and accuracy for temporal analysis.

    Potential Uses

    • Labor Market Analysis: Assist in understanding the employment dynamics in Canada, which is crucial for labor market forecasting and planning.
    • Human Resource Management: Provide insights into optimal workforce management practices for various industries.
    • Economic Policy: Support policymakers in monitoring and ensuring compliance with labor market trends and economic standards.
    • Industry-Specific Insights: Evaluate the impact of employment trends on specific industries and potential growth or decline areas.
    • Strategic Planning: Inform strategic planning for businesses and policymakers by providing a clear snapshot of current employment levels and trends.
  15. h

    logolens-industries

    • huggingface.co
    Updated Dec 22, 2024
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    Tiny Factories (2024). logolens-industries [Dataset]. https://huggingface.co/datasets/Tiny-Factories/logolens-industries
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 22, 2024
    Dataset authored and provided by
    Tiny Factories
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Dataset Name: LogoLens Industries

      Dataset Summary
    

    The logolens-industries dataset provides a comprehensive classification of industries based on the Global Industry Classification Standard (GICS). This dataset is designed for tasks such as industry-specific logo analysis, branding research, and AI-based categorization of visual or textual elements.

    Version: 1.0.0 Homepage: Hugging Face Dataset Page License: MIT

      Supported Tasks and Use Cases
    

    This dataset… See the full description on the dataset page: https://huggingface.co/datasets/Tiny-Factories/logolens-industries.

  16. o

    US BEA Employment by NAICS Industry

    • bfortune.opendatasoft.com
    • linc.osbm.nc.gov
    • +1more
    csv, excel, json
    Updated Aug 29, 2024
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    (2024). US BEA Employment by NAICS Industry [Dataset]. https://bfortune.opendatasoft.com/explore/dataset/us-bea-employment-by-naics-industry/
    Explore at:
    csv, excel, jsonAvailable download formats
    Dataset updated
    Aug 29, 2024
    Area covered
    United States
    Description

    Full-time and part-time employment by North American Industry Classification System (NAICS) industry.The US Bureau of Economic Analysis discontinued this dataset on November 14, 2024 due to budget constraints.

  17. D

    The changing face of business

    • data.nsw.gov.au
    • researchdata.edu.au
    • +1more
    Updated Jun 5, 2025
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    City of Sydney (2025). The changing face of business [Dataset]. https://www.data.nsw.gov.au/data/dataset/5-cityofsydney--the-changing-face-of-business-1
    Explore at:
    Dataset updated
    Jun 5, 2025
    Dataset provided by
    City of Sydney
    Description

    Explore business establishment data by industry from the 2007, 2012, 2017 and 2022 Floor space and Employment Survey (FES). The floor space and employment survey collects data on all businesses, floor space uses and employment numbers for every building or property in the City of Sydney local area every 5 years. The 2022 FES was the fourth full survey within the current City of Sydney local area boundaries. Previous surveys were undertaken in 2007, 2012 and 2017. Each business establishment is classified using a composite city-based industry classification to report on the various industry sectors across the local area, categorised by the main function of a business. The classifications are based on an expanded version of the Australian and New Zealand Standard Industrial Classification (ANZSIC) 2006. More information on the floor space and employment survey

  18. b

    Business Employer Directory 2023 Public

    • opendata.barrie.ca
    • public-barrie.opendata.arcgis.com
    • +1more
    Updated Jul 31, 2023
    + more versions
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    The City of Barrie (2023). Business Employer Directory 2023 Public [Dataset]. https://opendata.barrie.ca/datasets/business-employer-directory-2023-public/about
    Explore at:
    Dataset updated
    Jul 31, 2023
    Dataset authored and provided by
    The City of Barrie
    Area covered
    Description

    The City of Barrie conducted an extensive Business & Employer Data Survey. The business & employer data collected will give better insight into the City’s economic landscape and will help the City make more informed decisions that better support our businesses and residents. This data will allow the City to better monitor existing industry classifications, business sectors, business longevity and employment trends.Why is this survey important?The survey is important as it provides the City of Barrie with comprehensive business data, including:business name;location;employment numbers (both full-time and part-time); andindustry classifications.By collecting this data year to year, the City will be able to:monitor industry trends and levels of employment;inform other City initiatives, such as a review of infrastructure and servicing requirements, and transit planning; anddevelop a business directory of all local businesses.

  19. B2B Company Data API | Gain Comprehensive Firmographic Insights | Access...

    • datarade.ai
    Updated Feb 12, 2018
    + more versions
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    Success.ai (2018). B2B Company Data API | Gain Comprehensive Firmographic Insights | Access Profiles of 70M+ Companies | Best Price Guarantee [Dataset]. https://datarade.ai/data-products/b2b-company-data-api-gain-comprehensive-firmographic-insigh-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Feb 12, 2018
    Dataset provided by
    Area covered
    Kuwait, Mauritania, Tunisia, Italy, Armenia, Tokelau, Solomon Islands, Korea (Democratic People's Republic of), Malta, Iceland
    Description

    Success.ai’s B2B Company Data API provides direct, on-demand access to in-depth firmographic insights for over 70 million companies worldwide. Covering key attributes such as industry classification, company size, revenue ranges, and geographic footprints, this API ensures your sales, marketing, and strategic planning efforts are informed by accurate, continuously updated, and AI-validated data.

    Whether you’re evaluating new markets, refining your ICP (Ideal Customer Profile), or enhancing ABM campaigns, Success.ai’s B2B Company Data API delivers the intelligence needed to target the right organizations at the right time. Supported by our Best Price Guarantee, this solution empowers you to make data-driven decisions and gain a competitive edge in a complex global marketplace.

    Why Choose Success.ai’s B2B Company Data API?

    1. Comprehensive Global Coverage

      • Access profiles of over 70 million companies spanning multiple industries, sectors, and regions.
      • Confidently enter new markets, identify niche segments, and discover growth opportunities across the globe.
    2. AI-Validated Accuracy

      • Benefit from 99% data accuracy through AI-driven validation, ensuring every insight is reliable and actionable.
      • Trust that your decisions are backed by current, high-quality information, minimizing risk and guesswork.
    3. Continuous Data Updates

      • Real-time refreshes keep you aligned with evolving market conditions, organizational changes, and industry dynamics.
      • Always operate with the most relevant data, ensuring your outreach and strategies remain timely and impactful.
    4. Ethical and Compliant

      • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage for all applications.

    Data Highlights:

    • 70M+ Verified Company Profiles: Leverage a vast database to discover new accounts, refine targeting, and guide strategic initiatives.
    • Firmographic Insights: Gain visibility into industry classifications, company sizes, revenue tiers, and regional footprints.
    • Continuously Updated: Stay current with market expansions, mergers, and new entrants, seizing opportunities early.
    • Best Price Guarantee: Optimize ROI by accessing top-tier data at the most competitive prices on the market.

    Key Features of the B2B Company Data API:

    1. On-Demand Data Enrichment

      • Instantly enhance CRM records or marketing databases with verified company profiles, eliminating guesswork.
      • Maintain data hygiene and ensure teams always work with accurate, current intelligence.
    2. Advanced Filtering and Query Capabilities

      • Query the API to segment companies by industry, location, employee count, or revenue.
      • Zero in on the precise accounts that match your ideal customer profile, improving conversion and engagement rates.
    3. Real-Time Validation and Reliability

      • Rely on continuous data refreshes and AI validation for impeccable data integrity.
      • Reduce wasted effort and improve decision-making backed by trustworthy insights.
    4. Scalable and Flexible Integration

      • Seamlessly integrate the API into CRMs, analytics tools, or marketing platforms, streamlining workflows.
      • Adjust parameters as market conditions evolve, ensuring your data needs always match your strategic priorities.

    Strategic Use Cases:

    1. Account-Based Marketing (ABM)

      • Identify high-value accounts aligned with your ICP using firmographic data.
      • Deliver personalized outreach, increasing engagement, deal size, and overall ABM success.
    2. Market Expansion and Product Launches

      • Enter new markets with confidence by identifying industry leaders, rising players, and underserved segments.
      • Validate product-market fit and refine go-to-market strategies using data-driven insights.
    3. Competitive Benchmarking and Analysis

      • Monitor industry landscapes and track competitor growth to anticipate trends and pivot strategies proactively.
      • Stay ahead of market shifts by aligning solutions with evolving customer needs.
    4. Partner and Supplier Sourcing

      • Discover reliable partners, suppliers, or distributors based on firmographic filters.
      • Strengthen supply chains, reduce risks, and ensure stable growth through informed partner selection.

    Why Choose Success.ai?

    1. Best Price Guarantee

      • Access premium-quality B2B company data at industry-leading prices, maximizing ROI for data-driven initiatives.
    2. Seamless Integration

      • Incorporate the API into existing workflows easily, eliminating manual data imports and siloed processes.
    3. Data Accuracy with AI Validation

      • Rely on 99% accuracy to guide data-driven choices, refine targeting, and improve conversion rates.
    4. Customizable and Scalable Solutions

      • Tailor datasets to focus on particular industries, regions, or company sizes, adapting as your goals shift.

    Additi...

  20. d

    Canaria | Firmographic Data | USA | +26M Unique Companies & 2 Years...

    • datarade.ai
    Updated Mar 17, 2020
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    Canaria Inc. (2020). Canaria | Firmographic Data | USA | +26M Unique Companies & 2 Years Historical Firmographic Data | Industry classification with NAICS - SOC - SIC [Dataset]. https://datarade.ai/data-categories/firmographic-data/datasets
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Mar 17, 2020
    Dataset authored and provided by
    Canaria Inc.
    Area covered
    Gibraltar, Cyprus, Solomon Islands, Mexico, Nigeria, Peru, Cook Islands, Kuwait, Ghana, State of
    Description

    Detailed Data Dictionary: https://docs.google.com/spreadsheets/d/1Rvsb53lfYA00A2PJU22lSR44EBgtAThdeDrdhl_NGJk/edit?gid=1071313126gid=1071313126

    Advanced Processing, Superior Insights

    Utilizing state-of-the-art AI and large language models (LLMs) validated by human experts, we are dedicated to delivering high-quality, actionable data through innovative technology. Apart from the models included in our standard data offerings, we have developed additional models to provide tailored results to your needs, such as a sentiment analysis model that analyzes text data to gauge sentiment, helping businesses understand public perception and employee feedback, anomaly detection models, and LLM-based summarization models that condense large chunks of text for you.

    Our Models:

    • Deduplication Model: Our model first removes exact duplicate records, then uses advanced AI to identify and eliminate near-duplicate job postings across different URLs, achieving approximately a 60% deduplication rate.

    • Title Taxonomy Model: With over 20 million unique job titles in our 500M+ job postings database, analysis can be challenging. Our AI models categorize each job posting into one of 50,000 standardized job titles from our internal normalized title taxonomy, simplifying data analysis.

    • Skill Taxonomy Model: Our in-house AI model identifies key entities in job postings, including hard skills, soft skills, certifications, and qualifications. Unlike keyword-based approaches, our model not only finds relevant keywords but also excludes irrelevant ones, ensuring precise data (e.g., "Hepatitis B" is skill for nursing jobs but not for accounting jobs).

    • Job Category Model: Our AI models analyze job descriptions, entities, predicted salary, location, industry, and job title to determine the seniority level of a job, standardizing levels across different companies. Another model identifies if a job is remote, onsite, or hybrid, accounting for discrepancies between job classifications and descriptions (e.g., a job classified as onsite but open to remote).

    • Salary Estimation Model: Using company salary history, industry ranges, location, seniority, and public government data, our models predict the salary range for job postings.

    • Government Classification Models: We developed models to classify job postings into Standard Occupation Codes (SOC) by the BLS and to categorize companies into industries based on their job posting information.

    Canaria's Firmographic Data is unparalleled in its depth, accuracy, and comprehensiveness. Our firmographic data product offers detailed information on companies, including names, URLs, addresses, industries, revenues, employee counts, and more. We pride ourselves on the precision of our geographical firmographic data, including latitude, longitude, city, state, and zipcode information, which enables accurate location-based analysis.

    Our firmographic data is updated regularly, ensuring that users always have access to the most current and reliable information. This commitment to accuracy and relevance sets Canaria's Firmographic Data apart from other firmographic data products on the market. Furthermore, our extensive coverage spans a wide range of industries and countries, providing users with a global perspective that is essential for thorough market analysis and strategic decision-making.

    Canaria's Firmographic Data is sourced from a combination of public records, proprietary databases, industry reports, and direct submissions from companies. This multi-source approach ensures a high level of accuracy and completeness. We employ rigorous validation processes, including automated checks and manual reviews, to further enhance firmographic data quality. Our sourcing strategy not only ensures comprehensive coverage but also maintains the integrity and reliability of the firmographic data.

    Market Analysis:

    • Identify Emerging Trends: Use our firmographic data to uncover trends within specific industries and geographical regions. • Assess Market Dynamics: Gain a deep understanding of market conditions and competitive landscapes.

    Competitive Benchmarking:

    • Compare Against Industry Peers: Benchmark your company's performance metrics against those of industry leaders using our detailed firmographic data. • Gain Competitive Insights: Identify strengths and weaknesses relative to competitors.

    Targeted Marketing:

    • Segment and Target Clients: Utilize our firmographic data to create precise segments and target potential clients effectively. • Personalize Marketing Campaigns: Tailor your marketing strategies based on detailed firmographic profiles.

    Geographical Analysis:

    • Develop Location-Based Strategies: Leverage geographical firmographic data to identify optimal regions for business expansion and strategy development. • Analyze Regional Industry Distribution: Understand the distribution of industries across different regions.

    Academic Research:

    • Support Comprehensive Studies: Provide...

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Close
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data.melbourne.vic.gov.au (2021). Business establishments location and industry classification [Dataset]. https://data.gov.au/dataset/ds-melbourne-business-establishments-with-address-and-industry-classification

Business establishments location and industry classification

Explore at:
csv, json, shp, geojsonAvailable download formats
Dataset updated
Jan 11, 2021
Dataset provided by
data.melbourne.vic.gov.au
Description

Data collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data covers the period 2002-2023. It show business establishments with their business address, …Show full descriptionData collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data covers the period 2002-2023. It show business establishments with their business address, industry (ANZSIC4) classification, location and CLUE block and small area allocation. A business establishment is defined as a • Commercial occupant in a building • Separate land use • Any permanent presence of economic activity in accordance with standard Industry classification (ANZSIC). Hence, if one organisation has its presence in several buildings in the CLUE area, each time it will be counted as a separate establishment. Consequently, the count of establishments presented in CLUE represents the number of locations, rather than 'enterprises'. For more information about CLUE see http://www.melbourne.vic.gov.au/clue For more information about the ANZSIC industry classification system see http://www.abs.gov.au/ausstats/abs@.nsf/mf/1292.0

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