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TwitterThis data package consists of bioresearch monitoring information system (BMIS) dataset, directory of the different biotech and biopharmaceutical and pharmaceutical companies in the United States and the European Union, establishment registration database, drug wholesale distributor and third-party logistics provider reporting database, establishment inspections conducted by FDA, and FDA post-marketing requirements and commitments searchable database.
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TwitterFind details of Superior 3Rd Party Logistics In Ca Buyer/importer data in US (United States) with product description, price, shipment date, quantity, imported products list, major us ports name, overseas suppliers/exporters name etc. at sear.co.in.
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TwitterFrom our comprehensive UK Data Lake, we proudly present 5M+ high-quality UK decision-makers and influencers.
Take your ABM strategy to the next level, build a strong pipeline and close deals by laser targeting key decision-makers and influencers based on their department, job functions, job responsibilities, interest areas and expertise, then utilise essential prospect information, including verified work email addresses and business phone and social links.
Our data is sourced directly from executives, businesses, official sources and registries, standardised, de-duped, and verified, and then processed through vigorous compliance procedures for GDPR/PECR on a legitimate interest basis and RTBI etc. This results in a highly accurate single source of quality and compliant B2B data.
It is with our B2B Live Data Lake that we can enrich your CRM data, supply new prospect data, verify leads, and provide you with a custom dataset tailored to your target audience specifications. We also cater for big data licensing to software providers and agencies that intend to supply our data to their customers and use it in their software solutions.
and much more
Why Choose 1 Stop Data?
Products and Services:
The oscar4.io web platform for self-service data on demand Bulk data feeds Data hygiene, standardisation, cleansing and enrichment Know Your Business (KYB)
Keywords:
B2B,Prospect Data,Validated Work Emails,Personal Emails,Email Enrichment,Company Data,Lead Enrichment,Data Enhancement,Account Based Marketing (ABM),Customer Data,Phone Enrichment,LinkedIn URL,Market Intelligence,Business Intelligence,Data Append,Contact Data,Lead Generation,360-Degree Customer View,Data Cleansing,Lead Data,Email and Phone Validation,Data Augmentation,Segmentation,Data Enrichment,Email Marketing,Data Intelligence,Direct Marketing,Customer Insights,Audience Targeting,Audience Generation,Mobile Phone,B2B Data Enrichment,Social Advertising,Due Diligence,B2B Advertising,Audience Insights,B2B Lead Retargeting,Contact Information,Demographic Data,Consumer Data Enrichment,People-Based Marketing,Contact Data Enrichment,Customer Data Insights,Prospecting,Sales Intelligence,Predictive Analytics,Email Address Validation,Company Data Enrichment,Audience Intelligence,Cold Outreach,Analytics,Marketing Data Enrichment,Customer Acquisition,Data Cleansing,B2C Data,People Data,Professional Information,Recruiting and HR,KYC,B2B List Validation,Lead Information,Sales Prospecting,B2B Sales,B2B Data,Lead Lists,Contact Validation,Competitive Intelligence,Customer Data Enrichment,Identity Resolution,Identity Validation,Data Science,B2C Data Enrichment,B2C,Lead Data Enrichment,Social Media Data.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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HTTP client hint crawling data of all login pages of the 8M Tranco list websites.
This data set contains the crawled Accept-CH HTTP header values on all Tranco-list-related login pages from August 2022 to December 2023. You can use the data set to reproduce our study results regarding the client hint usage on the Web.
We crawled the data from three different continents (North America: Johnstown, Ohio, USA; Europe: Frankfurt and Biere, Germany; Asia: Singapore) and two different Internet Service Providers (ISP), which were Amazon Web Services (AWS) and Deutsche Telekom (DT).
You can find the crawling data inside the crawl_data_redacted folder of this repository. It is subdivided into our four different crawling regions, which are also the subfolders:
eu_otc: Crawling data from Biere, Germany (Europe), using the DT ISP.eu_aws: Crawling data from Frankfurt, Germany (Europe), using the AWS ISP.ap_aws: Crawling data from Singapore (Asia), using the AWS ISP.us_aws: Crawling data from Johnstown, Ohio, USA (North America), using the AWS ISP.Each folder includes the following files:
crawl_data_login_urls_only.csv: Contains the responses from all crawled login URLscrawl_data_clustered_third_party_urls_only.csv: Contains the responses from requests to third party URLs that were initiated by the login URLscrawl_data_trackerlist_urls_only.csv: Contains the responses from requests to third-party URLs that were identified as trackers and initiated by the login URLs.Each data set file contains the following columns:
| Column | Data Type | Description | Example |
|---|---|---|---|
| date | Timestamp | Point in time when the URL was crawled | 2023-03-03 14:45:25.525 |
| login_url | String | Uniform Resource Locator (URL) of the login URL that should be crawled | https://www.example.com/login.html |
| login_url_hostname | String | Hostname belonging to the crawled login URL | www.example.com |
| url | String | The actual URL that was crawled. In case it differs from login_url, it indicates a third party request. | https://www.example.com/index.html |
| url_hostname | String | Hostname belonging to the URL | www.example.com |
| Accept-CH Values (many columns) | Integer | The column name shows the corresponding value that was present in the Accept-CH HTTP Header (e.g., sec-ch-ua-platform). Its value shows whether this value was present (1) or not (0) | 1 - 0 |
We used the Tranco List from June 21st, 2022 and visited all 8M hostnames of this list with a crawler bot to identify their login pages. We then crawled the login pages on a monthly basis and recorded the Accept-CH HTTP header sent by each website. For technical reasons, we had crawling gaps of one (October 2022) and two months (October/November 2023). However, the impact should be minimal (see Publication).
You can find more details on our conducted study in the following journal article:
A Privacy Measure Turned Upside Down? Investigating the Use of HTTP Client Hints on the Web
Stephan Wiefling, Marian Hönscheid, and Luigi Lo Iacono.
19th International Conference on Availability, Reliability and Security (ARES '24), Vienna, Austria
...
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TwitterCC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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RCS Data Indonesia is a special tool that provides accurate information about RCS users. You can easily filter this data by gender, age, and relationship status. This tool lets you find exactly what you want. We follow GDPR rules to protect user privacy and keep personal information safe. Our team checks every entry carefully. We remove incorrect data, so you always see updated and accurate information. With this database, you will have the latest details about this data user, all organized easily. Moreover, RCS Data Indonesia is a collection of user data from trusted sources. It gets regular updates, so you won’t worry about old information. This database works well for businesses, researchers, and anyone looking for clear details. This database keeps everything simple and effective while following privacy rules. You can trust this tool to help you learn more about these data users easily. Indonesia RCS data stores data about RCS services. It helps mobile carriers, service providers, and third-party apps manage and analyze communication. Thus, it improves the RCS ecosystem’s efficiency. This data gives you 100% correct information about this data user. We can assist you in understanding or finding what you need. It has a replacement guarantee, so you will always get valid, up-to-date data. Each user shares their information with permission. This means you won’t have privacy issues. With this data, you can do great work on your projects or businesses. However, Indonesia RCS data follows high standards. It makes sure each piece is clear and correct. This data works well for businesses or individuals who need accurate information. You can connect effectively and responsibly with these users. This resource is really helpful for your research or projects. It gives you the information you need safely. Overall, this data is reliable and useful. It helps you understand RCS users better.
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TwitterDatabase of 434 licensed Third Party Providers under PSD2 regulation
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TwitterView details of Phor import data and shipment reports in US with product description, price, date, quantity, major us ports, countries and US buyers/importers list, overseas suppliers/exporters list.
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TwitterAmazon not only boasts a hugely successful online retail platform but also a thriving digital marketplace, which is seamlessly integrated with the main retail shopping experience. That being said, in the fourth quarter of 2025, ** percent of paid units were sold by third-party sellers. 1P and 3P Amazon sellers There are many ways of selling on Amazon. Firstly there are first-party (1P) vendor sales, where vendors send their inventory to Amazon, who in turn control the pricing and include “ships from and sold by Amazon.com” on product listings. The benefits of 1P sales on Amazon are wholesale purchases from Amazon, priority selling and brand trust through Amazon’s credibility as a seller. Amazon also permits third-party (3P) sales on its marketplace. Both individuals and professional sellers can sell on Amazon Marketplace. When it comes to order fulfillment, possible options are Fulfillment by Amazon (FBA) and Fulfillment by Merchant (FBM). Items are displayed as “sold by MERCHANT and Fulfilled by Amazon / Fulfilled by MERCHANT”. 3P sales are a popular strategy for sellers to make up for certain 1P sales disadvantages, namely improved margins through better pricing control, more favorable payment terms and less reliance on the relationship with Amazon. Amazon seller revenues This magic formula has ultimately cashed in for Amazon, which has seen its net revenues multiply in recent years. In 2024, the e-commerce giant generated approximately *** billion dollars in third-party seller services, an increase of about ** billion dollars from the previous year. While these figures are the product of orders throughout the year, a significant chunk is attributable to special offer and discount days. According to a survey, Black Friday is the shopping event driving the largest sales increase for Amazon sellers, followed by two of the company's own events, Prime Day and Amazon Summer Sale. In the context of the coronavirus pandemic, Amazon Prime Day played a particularly decisive role for small and medium-sized businesses around the world, many of which had to turn to online sales overnight in order to survive.
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Twitterhttps://www.technavio.com/content/privacy-noticehttps://www.technavio.com/content/privacy-notice
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Twitterhttps://www.mordorintelligence.com/terms-and-conditionshttps://www.mordorintelligence.com/terms-and-conditions
Our comprehensive proprietary performance metrics of key Data Center Power players beyond traditional revenue and ranking measures
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Twitterhttps://www.gesis.org/en/institute/data-usage-termshttps://www.gesis.org/en/institute/data-usage-terms
The goal of this study was to measure the attitudes towards data sharing and data-collecting organizations before and after the introduction of the EU General Data Protection regulations (GDPR) among people in Germany. The data come from a three-wave split-panel web survey among people 18 years and older in Germany who were recruited from a German nonprobability online panel. In April 2018 (before the GDPR came into effect), 2,095 participants completed the Wave 1 questionnaire on device ownership, social media use, trust in different data collecting organizations, willingness to share data, general trust, awareness of and knowledge about the GDPR, and privacy concerns. In July and in October 2018 (after the GDPR came into effect), respondents from the earlier waves were invited to participate in a second and a third web survey that repeated most of the questions from the first wave. In addition to participants from the earlier waves, fresh respondents were also invited to Waves 2 and 3. A total of 2,046 (Wave 2) and 2,117 (Wave 3) respondents completed the questionnaire in the subsequent waves. 1,269 participated in all three waves.
Topics:
Wave 1
Possession of smartphone, mobile phone, PC, tablet and/or e-book reader; social media use: account with user name and password at selected providers (Google, Facebook, Twitter, LinkedIn, Xing); trust in institutions (Google, Facebook, Bundesamt für Statistik, Universitätsforscher) with regard to the protection of personal data and reasons for this assessment; probability scale with regard to the protection of personal data at the above-mentioned institutions and reasons for this assessment; agreement with the import of personal data of the social insurance institutions to the survey data; general personal trust; awareness of the EU General Data Protection regulations (GDPR) ; knowledge test: goals of the GDPR (open); feeling of invaded privacy by the following institutions: Google, Facebook, government agencies, university researchers; general privacy concerns.
Wave 2
Possession of smartphone, mobile phone, PC, tablet and/or e-book reader; social media use: account with user name and password with selected providers (Google, Facebook, Twitter, LinkedIn, Xing); trust in institutions (Google, Facebook, Federal Statistical Office, university researchers) with regard to the protection of personal data; general personal trust; awareness of the EU General Data Protection regulations (GDPR); knowledge test: goals of the GDPR (open); consent to the storage of various personal data by Facebook or Google (name, e-mail address, home address, date of birth, telephone number, income, marital status, number of children, current location, Internet browser history, account names from other social media and data received from third parties); feeling of invasion of privacy by the following institutions: Google, Facebook, government agencies, university researchers; general privacy concerns.
Wave 3
Possession of smartphone, mobile phone, PC, tablet and/or e-book reader; social media use: account with user name and password at selected providers (Google, Facebook, Twitter, LinkedIn, Xing); trust in institutions (Google, Facebook, Federal Statistical Office, university researchers) with regard to the protection of personal data; general personal trust; awareness of the EU General Data Protection regulations (GDPR); knowledge test: goals of the GDPR (open); concerns about privacy in general; comprehensibility of excerpts of the contents of the EU General Data Protection regulations (GDPR) (resp. on passenger rights in the event of denied boarding and flight delays); estimated popularity of smartphones (proportion of smartphone owners per 100 adult Germans); repetition of the question on trust data collecting organisations (Google, Facebook) with regard to the protection of personal data and general personal trust; readiness for data exchange by Google (or Facebook or the Federal Statistical Office) for research purposes (or for commercial purposes).
Demography: sex; age (year of birth); federal state; school education; professional qualification.
Additionally coded was: running number; respondent ID; experimental groups GDPR Info; duration (reaction time in seconds); used device type to complete the questionnaire.
The questionnaire also included two experiments, one on the effect of GDPR-related information on trust in data collecting organisations and one on the comfort of data shar...
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Analyze 24 Third, Party export shipments from India to Qatar till Nov-25. Export data includes Buyers, Suppliers, Pricing, Qty & Contacts.
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TwitterFrom our comprehensive US Data Lake, we proudly present 8M+ high-quality enhanced US decision-makers and influencers.
Take your ABM strategy to the next level, build a strong pipeline and close deals by laser targeting key decision-makers and influencers based on their department, job functions, job responsibilities, interest areas and expertise, then utilise essential prospect information, including verified work email addresses and business phone and social links.
Our data is sourced directly from executives, businesses, official sources and registries, standardised, de-duped, and verified, and then processed through vigorous compliance procedures for GDPR/PECR on a legitimate interest basis and RTBI etc. This results in a highly accurate single source of quality and compliant B2B data.
It is with our B2B Live Data Lake that we can enrich your CRM data, supply new prospect data, verify leads, and provide you with a custom dataset tailored to your target audience specifications. We also cater for big data licensing to software providers and agencies that intend to supply our data to their customers and use it in their software solutions.
and much more
Why Choose 1 Stop Data?
Products and Services:
The oscar4.io web platform for self-service data on demand Bulk data feeds Data hygiene, standardisation, cleansing and enrichment Know Your Business (KYB)
Keywords:
B2B,Prospect Data,Validated Work Emails,Personal Emails,Email Enrichment,Company Data,Lead Enrichment,Data Enhancement,Account Based Marketing (ABM),Customer Data,Phone Enrichment,LinkedIn URL,Market Intelligence,Business Intelligence,Data Append,Contact Data,Lead Generation,360-Degree Customer View,Data Cleansing,Lead Data,Email and Phone Validation,Data Augmentation,Segmentation,Data Enrichment,Email Marketing,Data Intelligence,Direct Marketing,Customer Insights,Audience Targeting,Audience Generation,Mobile Phone,B2B Data Enrichment,Social Advertising,Due Diligence,B2B Advertising,Audience Insights,B2B Lead Retargeting,Contact Information,Demographic Data,Consumer Data Enrichment,People-Based Marketing,Contact Data Enrichment,Customer Data Insights,Prospecting,Sales Intelligence,Predictive Analytics,Email Address Validation,Company Data Enrichment,Audience Intelligence,Cold Outreach,Analytics,Marketing Data Enrichment,Customer Acquisition,Data Cleansing,B2C Data,People Data,Professional Information,Recruiting and HR,KYC,B2B List Validation,Lead Information,Sales Prospecting,B2B Sales,B2B Data,Lead Lists,Contact Validation,Competitive Intelligence,Customer Data Enrichment,Identity Resolution,Identity Validation,Data Science,B2C Data Enrichment,B2C,Lead Data Enrichment,Social Media Data.
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TwitterDRAKO is a Mobile Location Audience Data provider with a programmatic trading desk specialising in geolocation analytics and programmatic advertising. Through our customised approach, we offer business and consumer insights as well as addressable audiences for advertising.
Mobile Location Data can be meaningfully transformed into Audience Data when used in conjunction with other dataset. Our expansive POI Data allows us to segment users by visitation to major brands and retailers as well as categorizes them into syndicated segments. Beyond POI visits, our proprietary Home Location Model determines residents of geographic areas such as Designated Market Areas, Counties, or States. Relatedly, our Home Location Model also fuels our Geodemographic Census Data segments as we are able to determine residents of the smallest census units. Additionally, we also have audiences of: ticketed event and venue visitors; survey data; and retail data.
All of our Audience Data is 100% deterministic in that it only includes high-quality, real visits to locations as defined by a POIs satellite imagery buildings contour. We never use a radius when building an audience unless requested.
Overview of our Syndicated Audience Data Segments: - Brand/POI segments (specific named stores and locations) - Categories (behavioural segments - revealed habits) - Census demographic segments (HH income, race, religion, age, family structure, language, etc.,) - Events segments (ticketed live events, conferences, and seminars) - Resident segments (State/province, CMAs, DMAs, city, county, sub-county) - Political segments (Canadian Federal and Provincial, US Congressional Upper and Lower House, US States, City elections, etc.,) - Survey Data (Psychosocial/Demographic survey data) - Retail Data (Receipt/transaction data)
All of our syndicated segments are customizable. That means you can limit them to people within a certain geography, remove employees, include only the most frequent visitors, define your own custom lookback, or extend our audiences using our Home, Work, and Social Extensions.
In addition to our syndicated segments, we’re also able to run custom queries return to you all the Mobile Ad IDs (MAIDs) seen at in a specific location (address; latitude and longitude; or WKT84 Polygon) or in your defined geographic area of interest (political districts, DMAs, Zip Codes, etc.,)
Beyond just returning all the MAIDs seen within a geofence, we are also able to offer additional customizable advantages: - Average precision between 5 and 15 meters - CRM list activation + extension - Extend beyond Mobile Location Data (MAIDs) with our device graph - Filter by frequency of visitations - Home and Work targeting (retrieve only employees or residents of an address) - Home extensions (devices that reside in the same dwelling from your seed geofence) - Rooftop level address geofencing precision (no radius used EVER unless user specified) - Social extensions (devices in the same social circle as users in your seed geofence) - Turn analytics into addressable audiences - Work extensions (coworkers of users in your seed geofence)
Data Compliance: All of our Audience Data is fully CCPA compliant and 100% sourced from SDKs (Software Development Kits), the most reliable and consistent mobile data stream with end user consent available with only a 4-5 day delay. This means that our location and device ID data comes from partnerships with over 1,500+ mobile apps. This data comes with an associated location which is how we are able to segment using geofences.
Data Quality: In addition to partnering with trusted SDKs, DRAKO has additional screening methods to ensure that our mobile location data is consistent and reliable. This includes data harmonization and quality scoring from all of our partners in order to disregard MAIDs with a low quality score.
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TwitterThis data package consists of bioresearch monitoring information system (BMIS) dataset, directory of the different biotech and biopharmaceutical and pharmaceutical companies in the United States and the European Union, establishment registration database, drug wholesale distributor and third-party logistics provider reporting database, establishment inspections conducted by FDA, and FDA post-marketing requirements and commitments searchable database.