100+ datasets found
  1. People Data Labs Company Dataset

    • datarade.ai
    .json, .csv
    Updated Oct 18, 2021
    + more versions
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    People Data Labs (2021). People Data Labs Company Dataset [Dataset]. https://datarade.ai/data-products/people-data-labs-company-dataset-people-data-labs
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Oct 18, 2021
    Dataset provided by
    People Data Labs Inc.
    Authors
    People Data Labs
    Area covered
    Tokelau, Christmas Island, Romania, Martinique, Dominican Republic, Paraguay, Antarctica, South Sudan, Slovenia, Barbados
    Description

    People Data Labs is an aggregator of B2B person and company data. We source our globally compliant person dataset via our "Data Union".

    The "Data Union" is our proprietary data sharing co-op. Customers opt-in to sharing their data and warrant that their data is fully compliant with global data privacy regulations. Some data sources are provided as a one time dump, others are refreshed every time we do a new data build. Our data sources come from a variety of verticals including HR Tech, Real Estate Tech, Identity/Anti-Fraud, Martech, and others. People Data Labs works with customers on compliance based topics. If a customer wishes to ensure anonymity, we work with them to anonymize the data.

    Our company data has identifying information (name, website, social profiles), company attributes (industry, size, founded date), and tags + free text that is useful for segmentation.

  2. Justice Data Lab statistics: April 2023

    • s3.amazonaws.com
    • gov.uk
    Updated Apr 27, 2023
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    Ministry of Justice (2023). Justice Data Lab statistics: April 2023 [Dataset]. https://s3.amazonaws.com/thegovernmentsays-files/content/185/1858784.html
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    Dataset updated
    Apr 27, 2023
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Justice
    Description

    The report is released by the Ministry of Justice and produced in accordance with arrangements approved by the UK Statistics Authority.

    For further information about the Justice Data Lab, please refer to the following guidance:

    http://www.justice.gov.uk/justice-data-lab" class="govuk-link">http://www.justice.gov.uk/justice-data-lab

    Key findings this quarter

    One request is being published this quarter: The Chrysalis Programme (2012-2017).

    The Chrysalis Programme (2012-2017)

    The Chrysalis Programme is an integrated personal leadership and effectiveness development programme, working with individuals while they are in prison. This is the first JDL evaluation for Chrysalis, looking at programme participants between 2012 and 2017.

    The overall results show that those who took part in the Chrysalis Programme had a lower offending frequency compared to a matched comparison group. More people would be needed to determine the effect on the rate of reoffending and the time to first proven reoffence.

    Justice Data Lab service: available reoffending data

    The Justice Data Lab team have brought in reoffending data for the first quarter of 2021 into the service. It is now possible for an organisation to submit information on the individuals it was working with up to the end of March 2021, in addition to during the years 2002 to 2020.

    Pre-release access

    The bulletin is produced and handled by the Ministry’s analytical professionals and production staff. Pre-release access of up to 24 hours is granted to the following persons: Minister of State, Lord Chancellor and Secretary of State for Justice, Special Advisers, Permanent Secretary, Head of News, 1 Director General, 4 press officers, 2 policy officials, and 6 analytical officials. Relevant Special Advisers and Private Office staff of Ministers and senior officials may have access to pre-release figures to inform briefing and handling arrangements.

  3. Justice Data Lab statistics: April 2022

    • gov.uk
    • s3.amazonaws.com
    Updated Apr 28, 2022
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    Ministry of Justice (2022). Justice Data Lab statistics: April 2022 [Dataset]. https://www.gov.uk/government/statistics/justice-data-lab-statistics-april-2022
    Explore at:
    Dataset updated
    Apr 28, 2022
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Justice
    Description

    The report is released by the Ministry of Justice and produced in accordance with arrangements approved by the UK Statistics Authority. For further information about the Justice Data Lab, please refer to the guidance.

    Key findings this quarter

    One request is being published this quarter: Spark Inside (2016-2018).

    Spark Inside

    Spark Inside works with young male offenders, who are within 6 months of the end of their custodial sentence. This is the first JDL evaluation for Spark Inside, looking at programme participants between 2016 and 2018.

    The overall results do not show that the programme had a statistically significant effect on a person’s reoffending behaviour. They suggest more people need to be available for analysis to determine the way in which the programme affects the one-year proven reoffending rate, the frequency of proven reoffences, and the time taken to reoffend.

    Justice Data Lab service: available reoffending data

    The Justice Data Lab team have brought in reoffending data for the first quarter of 2020 into the service. It is now possible for an organisation to submit information on the individuals it was working with up to the end of March 2020, in addition to during the years 2002 to 2019.

    Pre-release access

    The bulletin is produced and handled by the Ministry’s analytical professionals and production staff. Pre-release access of up to 24 hours is granted to the following persons: Minister of State, Lord Chancellor and Secretary of State for Justice, Special Advisers, Permanent Secretary, Head of News, Deputy Head of News, 2 Director Generals, 5 press officers, 3 policy officials, and 10 analytical officials.

  4. p

    Global Data Lab Subnational Human Development (PRIO mirror)

    • prio.org
    Updated Jan 28, 2025
    + more versions
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    Peace Research Institute Oslo (PRIO) (2025). Global Data Lab Subnational Human Development (PRIO mirror) [Dataset]. http://doi.org/10.1038/sdata.2019.38
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    Dataset updated
    Jan 28, 2025
    Dataset provided by
    Peace Research Institute Oslo (PRIO)
    Time period covered
    1990 - 2022
    Area covered
    Global
    Description

    PRIO is hosting a copy of this dataset with permission from Global Data Lab. Please see their webpage for more information about this data.

  5. R

    Hw2 Data Lab Dataset

    • universe.roboflow.com
    zip
    Updated May 30, 2023
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    class (2023). Hw2 Data Lab Dataset [Dataset]. https://universe.roboflow.com/class-ock4y/hw2-data-lab/dataset/1
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    zipAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset authored and provided by
    class
    License

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

    Variables measured
    Digits
    Description

    Hw2 Data Lab

    ## Overview
    
    Hw2 Data Lab is a dataset for classification tasks - it contains Digits annotations for 2,067 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  6. Justice Data Lab statistics: July 2022

    • s3.amazonaws.com
    • gov.uk
    Updated Jul 28, 2022
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    Ministry of Justice (2022). Justice Data Lab statistics: July 2022 [Dataset]. https://s3.amazonaws.com/thegovernmentsays-files/content/182/1826893.html
    Explore at:
    Dataset updated
    Jul 28, 2022
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Justice
    Description

    The report is released by the Ministry of Justice and produced in accordance with arrangements approved by the UK Statistics Authority. For further information about the Justice Data Lab, please refer to the guidance.

    Key findings this quarter

    One request is being published this quarter: The Clink (2017-2020).

    The Clink

    The Clink work with offenders who are within 6 to 18 months of the end of their custodial sentence. This is the fourth JDL evaluation for The Clink, looking at programme participants who were released from prison between 2017 and Q2 2020. The previous analysis was published in July 2019.

    The overall results show that those who took part in The Clink intervention had a lower offending frequency compared to a matched comparison group. More people would be needed to determine the effect on the rate of reoffending and the time to first proven reoffence.

    Pre-release access

    The bulletin is produced and handled by the Ministry’s analytical professionals and production staff. Pre-release access of up to 24 hours is granted to the following persons: Minister of State, Lord Chancellor and Secretary of State for Justice, Special Advisers, Permanent Secretary, Head of News, Deputy Head of News, 2 Director Generals, 8 press officers, and 9 policy and analytical advisers.

  7. Data from: Assignment-1a

    • kaggle.com
    Updated Sep 21, 2020
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    Fadi Kelada (2020). Assignment-1a [Dataset]. https://www.kaggle.com/fadikelada/assignment1a/metadata
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 21, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Fadi Kelada
    Description

    Context

    There's a story behind every dataset and here's your opportunity to share yours.

    Content

    Data from Game of Thrones series

    Acknowledgements

    We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

    Inspiration

    Your data will be in front of the world's largest data science community. What questions do you want to see answered?

  8. a

    Soil Characterization Data (Lab Data)

    • hub.arcgis.com
    • ngda-portfolio-community-geoplatform.hub.arcgis.com
    Updated Dec 7, 2022
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    USDA NRCS ArcGIS Online (2022). Soil Characterization Data (Lab Data) [Dataset]. https://hub.arcgis.com/documents/cedb886980ca462fbb114c082ea50ffb
    Explore at:
    Dataset updated
    Dec 7, 2022
    Dataset authored and provided by
    USDA NRCS ArcGIS Online
    Area covered
    Description

    Soil Characterization Data (Lab Data)There are several sources of data to download and metadata linked to this site. Tabular Only Microsoft AccessSQLiteTabular and SpatialSQLiteGeoPackageESRI File GeodatabaseCompanion Pedon (Morphological) DataSQLite GeoPackageESRI File GeodatabaseMIR Spectral LibrarySoils, soil survey investigations, soil characterization data, soil laboratory data, soil research data, physical soil data, chemical soil data, mineralogical soil data, pedon descriptions. The database of the Kellogg Soil Survey Laboratory (KSSL), National Soil Survey Center, currently contains analytical data for more than 50,000 pedons from around the world. Partial data for pedons currently being analyzed may be unavailable. Soil fertility measurements, such as those made by Agricultural Experiment Stations, were not made. Most of the data were obtained over the last 40 years. About 3/4 of the data is less than 20 years old. Analytical data for most of the pedons is fairly complete, according to the prevailing view of the research and characterization needs when the pedon was sampled. Generally, the kinds of analyses have increased over time.National Cooperative Soil Survey (NCSS) Soil Characterization Map App

  9. g

    Health index

    • globaldatalab.org
    • data.amerigeoss.org
    • +1more
    utf-8
    Updated Apr 2, 2019
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    Global Data Lab (2019). Health index [Dataset]. https://globaldatalab.org/shdi/table/healthindex/
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    utf-8Available download formats
    Dataset updated
    Apr 2, 2019
    Dataset authored and provided by
    Global Data Lab
    Time period covered
    1990 - 2022
    Description

    Health index

  10. Justice Data Lab statistics: July 2016

    • gov.uk
    Updated Jul 14, 2016
    + more versions
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    Ministry of Justice (2016). Justice Data Lab statistics: July 2016 [Dataset]. https://www.gov.uk/government/statistics/justice-data-lab-statistics-july-2016
    Explore at:
    Dataset updated
    Jul 14, 2016
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Justice
    Description

    The report is released by the Ministry of Justice and produced in accordance with arrangements approved by the UK Statistics Authority.

    For further information about the Justice Data Lab, please refer to the following guidance: http://www.justice.gov.uk/justice-data-lab" class="govuk-link">http://www.justice.gov.uk/justice-data-lab

    Key findings this month

    One request is being published this month. The request is for the organisation Langley House Trust, a Housing Association and charity who provide an accommodation and floating support service to offenders in the community in 20 Local Authority areas across England and Wales.

    This analysis follows on from a previous analysis of data provided by Langley House first published in December 2014 and focuses on those who received the service after getting a fine or conditional discharge. The results indicate an inconclusive impact on the main one year proven re-offending rate.

    The bulletin is produced and handled by the Ministry’s analytical professionals and production staff. Pre-release access of up to 24 hours is granted to the following persons: Ministry of Justice Secretary of State, Parliamentary Under-Secretary of State - Minister for Prisons, Probation and Rehabilitation, Minister of State for Civil Justice (Lords Minister), Permanent Secretary, Director General of Strategy and Change, 7 Policy Advisers for reducing re-offending and rehabilitation policy, and 2 special advisors, 3 press officers, and 5 private secretaries.

  11. Labs & technological inc USA Import & Buyer Data

    • seair.co.in
    Updated Nov 27, 2018
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    Seair Exim (2018). Labs & technological inc USA Import & Buyer Data [Dataset]. https://www.seair.co.in
    Explore at:
    .bin, .xml, .csv, .xlsAvailable download formats
    Dataset updated
    Nov 27, 2018
    Dataset provided by
    Seair Exim Solutions
    Authors
    Seair Exim
    Area covered
    United States
    Description

    Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

  12. G

    Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

    • gdr.openei.org
    • data.openei.org
    • +3more
    data
    Updated May 14, 2021
    + more versions
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    Chris Marone; Derek Elsworth; Jing Yang; Chris Marone; Derek Elsworth; Jing Yang (2021). Processed Lab Data for Neural Network-Based Shear Stress Level Prediction [Dataset]. http://doi.org/10.15121/1787545
    Explore at:
    dataAvailable download formats
    Dataset updated
    May 14, 2021
    Dataset provided by
    Geothermal Data Repository
    USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Program (EE-4G)
    Pennsylvania State University
    Authors
    Chris Marone; Derek Elsworth; Jing Yang; Chris Marone; Derek Elsworth; Jing Yang
    License

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

    Description

    Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a non-overlapping window from the original acoustic data. The first column is the time of the window. The second and third columns are the mean and the variance of the acoustic data in this window, respectively. The 4th-11th column is the the power spectrum density ranging from low to high frequency. And the last column is the corresponding label (shear stress level). The name of the file means which driving velocity the sequence is generated from. Data were generated from laboratory friction experiments conducted with a biaxial shear apparatus. Experiments were conducted in the double direct shear configuration in which two fault zones are sheared between three rigid forcing blocks. Our samples consisted of two 5-mm-thick layers of simulated fault gouge with a nominal contact area of 10 by 10 cm^2. Gouge material consisted of soda-lime glass beads with initial particle size between 105 and 149 micrometers. Prior to shearing, we impose a constant fault normal stress of 2 MPa using a servo-controlled load-feedback mechanism and allow the sample to compact. Once the sample has reached a constant layer thickness, the central block is driven down at constant rate of 10 micrometers per second. In tandem, we collect an AE signal continuously at 4 MHz from a piezoceramic sensor embedded in a steel forcing block about 22 mm from the gouge layer The data from this experiment can be used with the deep learning algorithm to train it for future fault property prediction.

  13. e

    NSF NOIRLab Astro Data Lab TAP Service - Dataset - B2FIND

    • b2find.eudat.eu
    Updated Oct 14, 2024
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    (2024). NSF NOIRLab Astro Data Lab TAP Service - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/e6768266-022c-5f0d-be42-6b455358b3f5
    Explore at:
    Dataset updated
    Oct 14, 2024
    Description

    The Astro Data Lab Table Access Protocol (TAP) service provides mechanisms to execute queries and inspect metadata for tables provided by Astro Data Lab.

  14. GOSU Data Lab UAB - turnover, revenue, profit | Okredo

    • okredo.com
    Updated Jul 13, 2025
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    Okredo (2025). GOSU Data Lab UAB - turnover, revenue, profit | Okredo [Dataset]. https://okredo.com/en-lt/company/gosu-data-lab-uab-304708081/finance
    Explore at:
    Dataset updated
    Jul 13, 2025
    Dataset authored and provided by
    Okredo
    License

    https://okredo.com/en-lt/general-ruleshttps://okredo.com/en-lt/general-rules

    Time period covered
    2020 - 2022
    Area covered
    Lithuania
    Variables measured
    Equity (€), Turnover (€), Net Profit (€), CurrentAssets (€), Non-current Assets (€), Amounts Payable And Liabilities (€)
    Description

    GOSU Data Lab UAB financial data: profit, annual turnover, paid taxes, sales revenue, equity, assets (long-term and short-term), profitability indicators.

  15. Justice Data Lab statistics: November 2013

    • gov.uk
    Updated Nov 15, 2013
    + more versions
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    Ministry of Justice (2013). Justice Data Lab statistics: November 2013 [Dataset]. https://www.gov.uk/government/statistics/justice-data-lab-statistics-november-2013
    Explore at:
    Dataset updated
    Nov 15, 2013
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Justice
    Description

    Introduction

    The Justice Data Lab has been launched as a pilot for one year from April 2013. During this year, a small team from Analytical Services within the Ministry of Justice will support organisations that provide offender services by allowing them easy access to aggregate re-offending data, specific to the group of people they have worked with. This will support organisations in understanding their effectiveness at reducing re-offending.

    The service model involves organisations sending the Justice Data Lab team details of the offenders they have worked with along with information about the specific intervention they have delivered. The Data Lab team then matches these offenders to MoJ’s central datasets and returns the re-offending rate of this particular cohort, alongside that of a control group of offenders with very similar characteristics in order to better identify the impact of the organisation’s work.

    There are two publication types:

    • A summary of the findings of the Justice Data Lab pilot to date (2 April to 31 October 2013).

    • Tailored reports about the re-offending outcomes of services or interventions delivered by each of the organisations who have requested information through the Justice Data Lab pilot. Each report is an Official Statistic and will show the results of the re-offending analysis for the particular service or intervention delivered by the organisation who delivered it.

    Main findings to date

    9 To date, the Justice Data Lab has received 58 requests for re-offending information and has produced 7 reports which were published last month. A further 23 are now complete and ready for publication, bringing the total of completed reports to 30. To date, there have been 9 requests that could not be processed as the minimum criteria for analyses through the Data Lab had not been met. The remaining requests are currently in progress and will be published in future monthly releases of these statistics.

    Of the 23 reports being published this month:

    19 reports are regional analyses of the NOMS Co-Financing Organisation (NOMS CFO) project, which aims to help offenders access mainstream services with the aim of gaining skills and moving them into employment. The initiative is funded in partnership with the European Social Fund and is delivered regionally through a number of different suppliers; these include probation trusts and private companies such as Serco, A4E, and Pertemps People Development Group. There are 2 reports presented for each region where the programme was started by individuals in 2010; the first report for each region covers individuals who started the programme in custody, and the second report covers those who started whilst in the community.

    Of these 19 reports:

    • All the programmes which started in the community, with the exception of the North East, led to a reduction in the one year proven re-offending rate.
    • There were inconclusive findings for the programmes which started in custody.

    For further details about the NOMS CFO project, please see the following http://co-financing.org/about_main.php" class="govuk-link">information.

    There were four inconclusive results which looked at programmes delivered by Safe Ground, the Pre-School Learning Alliance in YOI Stoke, Riverside ECHG, and St Helens Integrated Offender Management (IOM). Reasons for an inconclusive result include; the sample of individuals provided by the organisation was too small to detect a statistically significant change in behaviour; or that the service or programme genuinely does not affect re-offending behaviour. However, it is very difficult to differentiate between these reasons in the analysis, so the organisations are recommended to submit larger samples of data when it becomes available. Detailed discussion of results and interpretation is available in the individual reports.

    The bulletin is produced and handled by the Ministry’s analytical professionals and production staff. Pre-release access of up to 24 hours is granted to the following persons: Ministry of Justice Secretary of State, Parliamentary Under Secretary of State, Permanent Secretary, Policy Advisers for reducing re-offending, Policy Advisors for the Transforming Rehabilitation Programme, and relevant Press Officers and Special Advisers.

  16. Lab design llc Import Company US

    • seair.co.in
    Updated Aug 15, 2017
    + more versions
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    Seair Exim (2017). Lab design llc Import Company US [Dataset]. https://www.seair.co.in
    Explore at:
    .bin, .xml, .csv, .xlsAvailable download formats
    Dataset updated
    Aug 15, 2017
    Dataset provided by
    Seair Exim Solutions
    Authors
    Seair Exim
    Area covered
    United States
    Description

    Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

  17. Intel Lab Data

    • kaggle.com
    Updated Dec 15, 2020
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    Caesar Lupum (2020). Intel Lab Data [Dataset]. https://www.kaggle.com/datasets/caesarlupum/iot-sensordata/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 15, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Caesar Lupum
    Description

    Dataset

    This dataset was created by Caesar Lupum

    Contents

  18. p

    X-Ray Labs in United States - 5,679 Verified Listings Database

    • poidata.io
    csv, excel, json
    Updated Jul 23, 2025
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    Poidata.io (2025). X-Ray Labs in United States - 5,679 Verified Listings Database [Dataset]. https://www.poidata.io/report/x-ray-lab/united-states
    Explore at:
    csv, excel, jsonAvailable download formats
    Dataset updated
    Jul 23, 2025
    Dataset provided by
    Poidata.io
    Area covered
    United States
    Description

    Comprehensive dataset of 5,679 X-ray labs in United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

  19. V

    Descartes Labs' Changes in Mobility data

    • data.virginia.gov
    html
    Updated Nov 22, 2024
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    Other (2024). Descartes Labs' Changes in Mobility data [Dataset]. https://data.virginia.gov/dataset/descartes-labs-changes-in-mobility-data
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    htmlAvailable download formats
    Dataset updated
    Nov 22, 2024
    Dataset authored and provided by
    Other
    Description

    Licensing on this dataset refers to GitHub content.

    See Descartes Labs' Terms of Service on their Web site for additional information. https://www.descarteslabs.com/terms-of-service/

  20. p

    X-Ray Labs in Alabama, United States - 90 Verified Listings Database

    • poidata.io
    csv, excel, json
    Updated Jul 3, 2025
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    Poidata.io (2025). X-Ray Labs in Alabama, United States - 90 Verified Listings Database [Dataset]. https://www.poidata.io/report/x-ray-lab/united-states/alabama
    Explore at:
    csv, json, excelAvailable download formats
    Dataset updated
    Jul 3, 2025
    Dataset provided by
    Poidata.io
    Area covered
    Alabama, United States
    Description

    Comprehensive dataset of 90 X-ray labs in Alabama, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Share
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People Data Labs (2021). People Data Labs Company Dataset [Dataset]. https://datarade.ai/data-products/people-data-labs-company-dataset-people-data-labs
Organization logo

People Data Labs Company Dataset

Explore at:
.json, .csvAvailable download formats
Dataset updated
Oct 18, 2021
Dataset provided by
People Data Labs Inc.
Authors
People Data Labs
Area covered
Tokelau, Christmas Island, Romania, Martinique, Dominican Republic, Paraguay, Antarctica, South Sudan, Slovenia, Barbados
Description

People Data Labs is an aggregator of B2B person and company data. We source our globally compliant person dataset via our "Data Union".

The "Data Union" is our proprietary data sharing co-op. Customers opt-in to sharing their data and warrant that their data is fully compliant with global data privacy regulations. Some data sources are provided as a one time dump, others are refreshed every time we do a new data build. Our data sources come from a variety of verticals including HR Tech, Real Estate Tech, Identity/Anti-Fraud, Martech, and others. People Data Labs works with customers on compliance based topics. If a customer wishes to ensure anonymity, we work with them to anonymize the data.

Our company data has identifying information (name, website, social profiles), company attributes (industry, size, founded date), and tags + free text that is useful for segmentation.

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