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

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

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

Products: API Suite Web UI Full and Custom Data Feeds

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

Amazon AWS - Cloud Platforms & Services

Companies using Amazon AWS

We have data on 1,070,574 companies that use Amazon AWS. The companies using Amazon AWS are most often found in United States and in the Computer Software industry. Amazon AWS is most often used by companies with 10-50 employees and 1M-10M dollars in revenue. Our data for Amazon AWS usage goes back as far as 2 years and 1 months.

What is Amazon AWS?

Amazon Web Services (AWS) is a collection of remote computing services, also called web services that make up a cloud computing platform offered by Amazon.com.

Top Industries that use Amazon AWS

Looking at Amazon AWS customers by industry, we find that Computer Software (6%) is the largest segment.

Distribution of companies using Amazon AWS by Industry

 Computer software - 67, 537 companies  Hospitals & Healthcare - 54, 293 companies  Retail - 39, 543 companies  Information Technology and Services - 35, 382 companies  Real Estate - 31, 676 companies  Restaurants - 30, 302 companies  Construction - 29, 207 companies  Automotive - 28, 469 companies  Financial Services - 23, 680 companies  Education Management - 21, 548 companies

Top Countries that use Amazon AWS

49% of Amazon AWS customers are in United States and 7% are in United Kingdom.

Distribution of companies using Amazon AWS by country

 United Sates – 616 2275 companies  United Kingdom – 68 219 companies  Australia – 44 601 companies  Canada – 42 770 companies  Germany – 31 541 companies  India – 30 949 companies  Netherlands – 19 543 companies  Brazil – 17 165 companies  Italy – 14 876 companies  Spain – 14 675 companies

Contact Information of Fields Include:-

• Company Name • Business contact number • Title
• Name • Email Address • Country, State, City, Zip Code • Phone, Mobile and Fax • Website • Industry • SIC & NAICS Code • Employees Size
• Revenue Size
• And more…

Why Buy AWS Users List from DataCaptive?

• More than 1,070,574 companies
• Responsive database • Customizable as per your requirements • Email and Tele-verified list • Team of 100+ market researchers • Authentic data sources

What’s in for you?

Over choosing us, here are a few advantages we authenticate-

• Locate, target, and prospect leads from 170+ countries • Design and execute ABM and multi-channel campaigns • Seamless and smooth pre-and post-sale customer service • Connect with old leads and build a fruitful customer relationship • Analyze the market for product development and sales campaigns • Boost sales and ROI with increased customer acquisition and retention

Our security compliance

We use of globally recognized data laws like –

GDPR, CCPA, ACMA, EDPS, CAN-SPAM and ANTI CAN-SPAM to ensure the privacy and security of our database. We engage certified auditors to validate our security and privacy by providing us with certificates to represent our security compliance.

Our USPs- what makes us your ideal choice?

At DataCaptive™, we strive consistently to improve our services and cater to the needs of businesses around the world while keeping up with industry trends.

• Elaborate data mining from credible sources • 7-tier verification, including manual quality check • Strict adherence to global and local data policies • Guaranteed 95% accuracy or cash-back • Free sample database available on request

Guaranteed benefits of our Amazon AWS users email database!

85% email deliverability and 95% accuracy on other data fields

We understand the importance of data accuracy and employ every avenue to keep our database fresh and updated. We execute a multi-step QC process backed by our Patented AI and Machine learning tools to prevent anomalies in consistency and data precision. This cycle repeats every 45 days. Although maintaining 100% accuracy is quite impractical, since data such as email, physical addresses, and phone numbers are subjected to change, we guarantee 85% email deliverability and 95% accuracy on other data points.

100% replacement in case of hard bounces

Every data point is meticulously verified and then re-verified to ensure you get the best. Data Accuracy is paramount in successfully penetrating a new market or working within a familiar one. We are committed to precision. However, in an unlikely event where hard bounces or inaccuracies exceed the guaranteed percentage, we offer replacement with immediate effect. If need be, we even offer credits and/or refunds for inaccurate contacts.

Other promised benefits

• Contacts are for the perpetual usage • The database comprises consent-based opt-in contacts only • The list is free of duplicate contacts and generic emails • Round-the-clock customer service assistance • 360-degree database solutions

List of web and marketing agencies in Martinique (972). ‘’ { “description” means: “Data descriptor for companies in Martinique and Guadeloupe”, “source”: “Data provided by the user”, “Fields”:[ { “name” means:“NAME”, ‘type’ means:“string”, “description” means: “The name of the company” }, { “name” means:“ADDRESS”, ‘type’ means: “string”, “description” means:“The main address of the company” }, { “name” means: “ADRESS2”, ‘type’ means: “string”, “description” means:“The secondary address of the undertaking, if applicable” }, { “name” means: “CPO”, ‘type’ means:“integer”, “description” means: “The company’s postal code” }, { “name” means: “CITY”, ‘type’ means:“string”, “description” means: The city where the company is located }, { “name” means:“PHONE1”, ‘type’ means: “string”, “description” means: “The company’s main telephone number” }, { “name” means:“PHONE2”, ‘type’ means: “string”, “description” means: “The company’s secondary telephone number” }, { “name” means:“EMAIL”, ‘type’ means:“string”, “description” means: “The company’s contact email address” }, { “name” means:“URL”, ‘type’ means: “string”, “description” means: “The URL of the company’s website” }, { “name” means: ‘TYPE’, ‘type’ means:“string”, “description” means: The type of business (Marketing, Web, etc.) } ], “format”:“JSON”, “Encoding”:“UTF-8” } ‘’ ‘’ { “description” means:“Data descriptor for companies in Martinique and Guadeloupe”, “source”: “Data provided by the user”, “Fields”: [ { “name” means: “NAME”, ‘type’ means:“string”, “description” means: “The name of the company” }, { “name” means: “ADDRESS”, ‘type’ means: “string”, “description” means:“The main address of the company” }, { “name” means:“ADRESS2”, ‘type’ means: “string”, “description” means: “The secondary address of the undertaking, if applicable” }, { “name” means:“CPO”, ‘type’ means: “integer”, “description” means:“The company’s postal code” }, { “name” means:“CITY”, ‘type’ means: “string”, “description” means:The city where the company is located }, { “name” means: “PHONE1”, ‘type’ means: “string”, “description” means:“The company’s main telephone number” }, { “name” means:“PHONE2”, ‘type’ means: “string”, “description” means: “The company’s secondary telephone number” }, { “name” means: “EMAIL”, ‘type’ means:“string”, “description” means: “The company’s contact email address” }, { “name” means: “URL”, ‘type’ means:“string”, “description” means: “The URL of the company’s website” }, { “name” means: ‘TYPE’, ‘type’ means: “string”, “description” means: The type of business (Marketing, Web, etc.) } ], “format”: “JSON”, “Encoding”:“UTF-8” } ‘’ ‘’ { “description” means: “Data descriptor for companies in Martinique and Guadeloupe”, “source”:“Data provided by the user”, “Fields”: [ { “name” means: “NAME”, ‘type’ means: “string”, “description” means:“The name of the company” }, { “name” means: “ADDRESS”, ‘type’ means: “string”, “description” means: “The main address of the company” }, { “name” means: “ADRESS2”, ‘type’ means:“string”, “description” means: “The secondary address of the undertaking, if applicable” }, { “name” means: “CPO”, ‘type’ means: “integer”, “description” means:“The company’s postal code” }, { “name” means: “CITY”, ‘type’ means:“string”, “description” means: The city where the company is located }, { “name” means:“PHONE1”, ‘type’ means: “string”, “description” means:“The company’s main telephone number” }, { “name” means: “PHONE2”, ‘type’ means: “string”,

“description” means: “The company’s secondary telephone number”

},

{

“name” means: “EMAIL”,

‘type’ means: “string”,

“description” means: “The company’s contact email address”

},

{

“name” means: “URL”,

‘type’ means: “string”,

“description” means: “The URL of the company’s website”

},

{

“name” means: ‘TYPE’,

‘type’ means: “string”,

“description” means: The type of business (Marketing, Web, etc.)

}

],

“format”: “JSON”,

“Encoding”: “UTF-8”

}

‘’

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

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

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

Products: API Suite Web UI Full and Custom Data Feeds

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

• 500K+ Active Amazon Stores • 200K+ Seller Leads • Platforms USA, Germany, UK, Italy, France, Spain, CA • C-Suite/Marketing/Sales Contacts • FBA/Non-FBA Sellers • 15+ data points available for each prospect • Filter your leads by store size, niche, location, and many more • 100% manually researched and verified.

For over a decade, we have been manually collecting Amazon seller data from various data sources such as Amazon, Linkedin, Google, and others. We are specialized to get valid, and potential data so you may conduct ads and begin selling without hesitation.

We designed our data packages for all types of organizations, thus they are reasonably priced. We are always trying to reduce our prices to better suit all of your requirements.

So, if you’re looking to reach out to your targeted Amazon sellers, now is the greatest time to do so and offer your goods, services, and promotions. You can get your targeted Amazon Sellers List with seller contact information.

Alternatively, if you provide Amazon Seller Names or IDs, we will conduct Custom Research and deliver the customized list to you.

Data Points Available:

Full Name Linkedin URL Direct Email Generic Phone Number Business Name and Address Company Website Seller IDs and URLs Revenue Seller Review Count Niche FBA/Non-FBA Country and More

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.

The 20,000+ registered companies with a registered address in Glasgow. The information is extracted from Companies House. It includes the company name, number, category (private limited, partnership), registered address, postcode, industry (SIC code), status (ex: active or liquidation), incorporation date... It is likely that some companies may just lie off Glasgow City Council's boundary. If you find a problem in the data, you can check the source either in the full UK list or by looking up a company or let us know. The data dictionary supplied by Companies House can be viewed here. There is also a data dictionary with field names and meanings contained in the resources. This dataset does not imply: - a partnership with Companies House - an endorsement by Companies House - a product approval by Companies House Licence: None glasgow-post-codes-py.txt - https://dataservices.open.glasgow.gov.uk/Download/Organisation/cc57ac4b-12d5-43b1-ad25-434638eec18c/Dataset/3093e34f-6dcb-4980-840b-965421c1b091/File/c2634107-bd43-4537-adb8-9046aeed844e/Version/c8fde78e-5396-4293-ac35-6f6c96a5d642

Massive eBay Marketplace Data Collection for E-commerce Intelligence

Unlock the power of online marketplace analytics with our comprehensive eBay products dataset. This premium collection contains 1.29 million products from eBay's global marketplace, providing extensive insights into one of the world's largest e-commerce platforms. Perfect for competitive analysis, pricing strategies, market research, and machine learning applications in e-commerce.

Dataset Overview

• Total Products: 1,290,000+ marketplace listings
• Source: eBay Global Marketplace
• Format: CSV, ZIP compressed
• File Size: Optimized compressed format
• Coverage: Multi-category product listings across eBay

Complete Data Fields Included

Product Identification

• id: Unique eBay product identifiers
• name: Complete product titles and names
• url: Direct eBay listing page links
• epid: eBay Product ID for catalog matching
• source: Data source identification

Product Details

• raw_product_description: Original unprocessed product descriptions
• product_description: Cleaned and formatted product descriptions
• brand: Brand names and manufacturer information
• mpn: Manufacturer Part Numbers
• gtin13: Global Trade Item Numbers (barcodes)

Pricing and Availability

• price: Current listing prices
• currency: Currency information for international listings
• in_stock: Stock availability status
• breadcrumbs: Category navigation paths

Visual and Technical Data

• images: Product image URLs and references
• crawled_at: Data collection timestamps

Key Use Cases

E-commerce Market Research

• Analyze eBay marketplace trends and patterns
• Study product category performance
• Monitor pricing strategies across sellers
• Identify high-demand product categories

Competitive Intelligence

• Benchmark pricing against eBay marketplace
• Analyze product positioning strategies
• Study seller competition and market share
• Monitor inventory levels and availability

Price Optimization

• Develop dynamic pricing algorithms
• Analyze price elasticity across categories
• Compare marketplace pricing trends
• Optimize listing prices for maximum visibility

Machine Learning Applications

• Train recommendation systems
• Develop price prediction models
• Create product categorization algorithms
• Build inventory forecasting systems

Target Industries

E-commerce Retailers

• Marketplace Strategy: Optimize eBay selling strategies
• Pricing Intelligence: Competitive price monitoring
• Product Research: Identify profitable product opportunities
• Inventory Planning: Demand forecasting and stock optimization

Technology Companies

• AI Training Data: Machine learning model development
• Analytics Platforms: E-commerce intelligence tools
• Price Comparison: Marketplace comparison services
• Search Enhancement: Product discovery optimization

Market Research Firms

• Industry Reports: E-commerce marketplace analysis
• Consumer Behavior: Online shopping pattern studies
• Brand Monitoring: Brand performance tracking
• Trend Analysis: Market trend identification

Academic Research

• E-commerce Studies: Online marketplace research
• Business Intelligence: Retail analytics case studies
• Data Science Projects: Large-scale dataset analysis
• Economic Research: Digital marketplace economics

Data Quality Features

• Comprehensive Coverage: 1.29 million unique products
• Rich Metadata: Complete product information included
• Validated Data: Quality-checked and processed
• Structured Format: Ready-to-use CSV format
• Global Scope: International marketplace coverage

In 2024, tech companies ranked as the most valuable brands in the world, covering the five top spots in the source’s ranking. Apple led the list with a brand value of nearly 489 billion U.S. dollars, followed by Microsoft, Amazon, and Google – each with brand values of over 290 billion dollars. Samsung closed the top five, at over 100 billion dollars in brand value. Big techs are also huge in terms of market value The source determined brand value by combining financial information, the role the brand plays in determining consumer choice (independent of other factors such as price and convenience), and a qualitative assessment of the brand’s overall strength. Considering only financial data, Apple, Amazon, Alphabet (Google’s parent company) and Microsoft would be still on the top, as they have some of the highest global market capitalizations. However, when considering only qualitative factors regarding brand strength, the list would look very different, with Chinese app WeChat being the strongest brand worldwide in 2024. Brand value vs. profitability Brand value does not always translate into profitability. While Apple also happens to be the second most profitable company in the world, other companies with strong brands such as Google and Amazon rank lower in terms of net income. This phenomenon does not only apply to tech companies – Coca-Cola did not feature on the list of the most profitable companies worldwide. This is likely due to their franchised distribution structure, whereby manufacturing operations are handled by separate companies, each of which operates independently with an exclusive license to manufacture Coca-Cola beverages in their territory.

This dataset offers a collection of customer reviews and ratings for data science-related books sourced from Amazon. It provides a valuable resource for understanding customer sentiment and the overall reception of various publications within the data science domain. The collection includes 20,647 individual reviews covering 836 distinct data science books. Each entry features the raw review text and a corresponding star rating, ranging from 1 to 5.

Columns

• stars: Represents the customer's rating for the book, indicated by a number from 1 to 5, where 5 is the highest possible score.
• comment: Contains the textual content of the customer's review.
• book_url: Provides the direct web address to the specific book's product page on Amazon.

Distribution

The dataset is structured as a CSV file and comprises 20,647 reviews. These reviews relate to 836 unique books identified through "Data Science" searches on Amazon. The star ratings are distributed across several bands: * 1.00 - 1.20 stars: 1,430 reviews * 2.00 - 2.20 stars: 929 reviews * 3.00 - 3.20 stars: 1,431 reviews * 4.00 - 4.20 stars: 2,894 reviews * 4.80 - 5.00 stars: 13,963 reviews

The dataset contains unique values for stars from 1 to 5 and for 836 books.

Usage

This dataset is well-suited for a variety of analytical and developmental purposes, including: * Natural Language Processing (NLP) tasks such as sentiment analysis, text classification, and topic modelling using the review comments. * Machine Learning (ML) model training for tasks like predicting book popularity or building recommendation engines. * Business intelligence applications to gain insights into consumer preferences and market trends for data science literature. * Research into review patterns, user feedback mechanisms, and e-commerce dynamics.

Coverage

The dataset has a global regional coverage. It was listed on 16/06/2025. No specific demographic or historical time range information beyond the listing date is available in the provided sources.

License

CCO

Who Can Use It

This dataset is particularly useful for: * Data Scientists and Machine Learning Engineers engaged in building and testing text-based analytical models. * Academic Researchers and Students focused on computational linguistics, consumer behaviour, or data science education. * Market Analysts and Business Strategists looking to understand product perception and competitive landscapes within the book industry. * Developers creating applications that require user-generated content for training or analysis.

Dataset Name Suggestions

• Amazon Data Science Book Reviews
• Data Science Book Customer Ratings Dataset
• Amazon DS Book Reviews and Ratings
• Data Science Book Feedback Collection

Attributes

Original Data Source: Amazon Data Science Book Reviews

Techsalerator’s Job Openings Data in Latin America provides a thorough and insightful dataset designed to deliver businesses, recruiters, labor market analysts, and job seekers with a comprehensive view of employment opportunities across the Latin American region. This dataset aggregates job postings from a diverse array of sources on a daily basis, ensuring that users have access to the most current and extensive collection of job openings available throughout Latin America.

Key Features of the Dataset: Extensive Coverage:

The dataset aggregates job postings from a variety of sources, including company career sites, job boards, recruitment agencies, and professional networking platforms. This comprehensive coverage ensures that users receive a broad spectrum of job opportunities from multiple channels. Daily Updates:

Data is updated daily, providing real-time insights into job market conditions. This frequent updating ensures that the dataset reflects the latest job openings and market trends. Sector-Specific Data:

Job postings are categorized by industry sectors such as technology, healthcare, finance, education, manufacturing, and more. This segmentation allows users to analyze trends and opportunities within specific industries. Regional Breakdown:

Detailed information is provided on job openings across different countries and key regions within Latin America. This regional breakdown helps users understand job market dynamics and opportunities in various geographic areas. Role and Skill Analysis:

The dataset includes information on job roles, required skills, qualifications, and experience levels. This feature assists job seekers in identifying opportunities that match their expertise and helps recruiters find candidates with the desired skill sets. Company Insights:

Users can access information about the companies posting job openings, including company names, industries, and locations. This data provides insights into which companies are hiring and where demand for talent is highest. Historical Data:

The dataset may include historical job posting data, enabling users to perform trend analysis and comparative studies over time. This feature supports understanding changes and developments in the job market. Latin American Countries Covered: South America: Argentina Bolivia Brazil Chile Colombia Ecuador Guyana Paraguay Peru Suriname Uruguay Venezuela Central America: Belize Costa Rica El Salvador Guatemala Honduras Nicaragua Panama Caribbean: Cuba Dominican Republic Haiti (Note: Primarily French-speaking, but included due to geographic and cultural ties) Jamaica Trinidad and Tobago Benefits of the Dataset: Strategic Recruitment: Recruiters and HR professionals can use the data to identify hiring trends, understand competitive practices, and optimize their recruitment strategies based on real-time market insights. Labor Market Analysis: Analysts and policymakers can leverage the dataset to study employment trends, identify skill gaps, and evaluate job market opportunities across different regions and sectors. Job Seeker Support: Job seekers can access a comprehensive and updated list of job openings tailored to their skills and preferred locations, enhancing the efficiency and effectiveness of their job search. Workforce Planning: Companies can gain valuable insights into the availability of talent across Latin America, assisting with decisions related to market entry, expansion, and talent acquisition. Techsalerator’s Job Openings Data in Latin America is an essential tool for understanding the diverse and evolving job markets across the region. By providing up-to-date and detailed information on job postings, it supports effective decision-making for businesses, job seekers, and labor market analysts.

This dataset presents the location of business listings from Sands & McDougall's Directory of Victoria. The data was created by digitising the published business directories using an Optical Character Recognition (OCR) process. The extracted information includes the business name, address and business type as listed in the Sands & McDougall directories. The address information was subsequently geocoded to provide a spatial location. The data spans the the Sands & McDougall's Directory of Victoria publication years 1896, 1925 and 1974. Victoria Unearthed is a collection of data which includes past and present information about historical businesses, potential land and groundwater contamination, as well as information about contamination management and cleanup activities. Victoria Unearthed has been created in response to the Independent Inquiry into the Environmental Protection Authority (EPA). For further information about this dataset, visit the data source:Government of Victoria - Department of Land, Water and Planning. Please note: Attributes captured by OCR ("directory address", "business name" and "business type") are uncorrected and may include errors. The positional accuracy is affected by the limitations inherent with OCR and geocoding. Some issues such as changing street names, are exacerbated by the age of the records. The directories were not consistent in the amount of information captured as the business address, in many cases it only lists the town or suburb for the business. A modern (July 2018) property address, street or locality as defined by VicMap has been captured for all records.

PredictLeads Technographic Data is a powerful tool for B2B organizations, providing detailed technographic and firmographic insights extracted through sophisticated web scraping techniques. Unlike traditional datasets, it identifies emerging technologies in job postings, revealing real-time technology adoption trends across industries. These insights fuel technical decision-making, B2B data cleansing, account profiling, and 360-degree customer analysis.

Use Cases:

✅ Technical Account Profiling – Analyze a company’s technology stack and hiring trends for better-targeted sales and marketing. ✅ B2B Data Cleansing – Enhance CRM and data enrichment efforts with up-to-date, verified technographic insights. ✅ Technology Trend Analysis – Identify high-growth industries and emerging tech adoption patterns. ✅ Competitive Intelligence – Assess competitor tech stacks and innovation roadmaps based on hiring activity. ✅ 360-Degree Customer View – Integrate firmographic and technographic data for a complete B2B customer profile.

Key API Attributes:

• id (string, UUID) – Unique identifier for the technology detection.
• first_seen_at (ISO 8601 date-time) – Date when the technology was first detected.
• last_seen_at (ISO 8601 date-time) – Last observed instance of the technology in use.
• technology (object) – Details about the detected technology:
• name (string) – Technology name (e.g., "AWS Lambda", "Kubernetes").
• company (object) – Data about the company using the technology:
• domain (string) – Company website domain.
• company_name (string) – Full company name.
• seen_on_job_openings (array, nullable) – List of job postings mentioning the technology, indicating hiring demand.
• seen_on_subpages (array) – URLs of web pages where the technology was detected, providing additional context.

📌 PredictLeads Technographic Data is the go-to solution for B2B professionals looking to optimize technical sales strategies, refine account targeting, and gain a competitive edge in technology-driven markets.

PredictLeads Docs: https://docs.predictleads.com/v3/guide/technology_detections_dataset

This dataset provides fine-grained financial sentiment analysis on news headlines. It is a human-annotated collection of over 10,700 news headlines, specifically designed to address the challenging task of sentiment extraction in financial news where multiple entities may be present, often with conflicting sentiments. Over 2,800 headlines within the dataset feature multiple entities. The dataset is balanced, containing more than 4,100 positive entities, 3,200 negative entities, and 4,500 neutral entities. It is ideal for furthering research in entity-aware sentiment analysis and can be used for training models for extracting financial named entities.

Columns

• S No.: Represents the serial number for each entry.
• Title: Contains the news headlines.
• Decisions: Provides the sentiment annotations for various financial entities identified within the news headlines.
• Words: Indicates the number of words in each news headline.

Distribution

The dataset is provided as a data file, typically in CSV format. It contains over 10,700 distinct news headlines. The structure includes human-annotated sentiment labels for financial entities, with sentiments balanced across positive, negative, and neutral categories. The dataset includes headlines with varying word counts, and its sentiment annotations are quite diverse, representing 10,686 unique values for entity sentiments.

Usage

This dataset is well-suited for several applications: * Performing Aspect-based Sentiment Analysis on financial texts. * Training machine learning models for the extraction of named financial entities. * Conducting research into fine-grained financial sentiment analysis. * Validating the effect of news sentiments on aggregate market movements. * Developing and evaluating learning schemes, including those utilising lexicon-based and pre-trained sentence representations, and various classification approaches.

Coverage

The dataset has a global regional coverage. While the listing date is 08/06/2025, the underlying research for SEntFiN 1.0 was published in 2022. The news headlines themselves do not specify a fixed time range within the provided information, focusing instead on the content and its annotations. No specific demographic scope is outlined, but the content is inherently focused on financial markets and related entities.

License

CC-BY

Who Can Use It

This dataset is beneficial for a range of users and purposes: * Researchers focusing on financial Natural Language Processing (NLP) and sentiment analysis. * Data Scientists and Analysts working on text classification, entity extraction, and market behaviour prediction. * Anyone involved in Business or Finance seeking to understand or model sentiment from news. * Developers of AI and Machine Learning models requiring human-annotated financial text data.

Dataset Name Suggestions

• SEntFiN 1.0
• Financial News Entity Sentiment Headlines
• Aspect-Based Financial Sentiment Data
• Annotated Financial News for NLP
• Financial News Sentiment Analysis Dataset

Attributes

Original Data Source: Aspect based Sentiment Analysis for Financial News

Techsalerator’s Job Openings Data in Africa offers a comprehensive and insightful dataset designed to provide businesses, recruiters, labor market analysts, and job seekers with a thorough view of employment opportunities across the African continent. This dataset aggregates job postings from a wide range of sources on a daily basis, ensuring that users have access to the most current and extensive collection of job openings available throughout Africa.

Key Features of the Dataset: Broad Coverage:

The dataset aggregates job postings from numerous sources including company career pages, job boards, recruitment agencies, and professional networking sites. This extensive coverage ensures a broad spectrum of job opportunities from multiple channels. Daily Updates:

Job posting data is updated daily, providing real-time insights into the job market. This frequent updating ensures that the dataset reflects the latest job openings and market trends. Sector-Specific Data:

Job postings are categorized by industry sectors such as technology, healthcare, finance, education, manufacturing, and more. This categorization allows users to analyze trends and opportunities within specific industries. Regional Breakdown:

The dataset includes detailed information on job openings across different countries and regions within Africa. This regional breakdown helps users understand job market dynamics and opportunities in various geographic locations. Role and Skill Insights:

The dataset includes information on job roles, required skills, qualifications, and experience levels. This feature assists job seekers in finding opportunities that match their expertise and helps recruiters identify candidates with the desired skill sets. Company Information:

Users can access details about the companies posting job openings, including company names, industries, and locations. This data provides insights into which companies are hiring and where the demand for talent is highest. Historical Data:

The dataset may include historical job posting data, enabling users to perform trend analysis and comparative studies over time. This feature supports understanding changes and developments in the job market. African Countries Covered: Northern Africa: Algeria Egypt Libya Mauritania Morocco Sudan Tunisia Sub-Saharan Africa: West Africa: Benin Burkina Faso Cape Verde Ivory Coast (Côte d'Ivoire) Gambia Ghana Guinea Guinea-Bissau Liberia Mali Niger Nigeria Senegal Sierra Leone Togo Central Africa: Angola Cameroon Central African Republic Chad Congo, Republic of the Congo, Democratic Republic of the Equatorial Guinea Gabon São Tomé and Príncipe East Africa: Burundi Comoros Djibouti Eritrea Eswatini (Swaziland) Ethiopia Kenya Lesotho Malawi Mauritius Rwanda Seychelles Somalia Tanzania Uganda Southern Africa: Botswana Lesotho Namibia South Africa Swaziland (Eswatini) Zimbabwe Benefits of the Dataset: Enhanced Recruitment Strategies: Recruiters and HR professionals can use the dataset to identify hiring trends, understand competitive practices, and refine recruitment strategies based on real-time market insights. Labor Market Analysis: Analysts and policymakers can leverage the dataset to study employment trends, identify skill gaps, and evaluate job market opportunities across different regions and sectors. Job Seeker Support: Job seekers can access a comprehensive and updated list of job openings tailored to their skills and preferred locations, making their job search more efficient and targeted. Strategic Workforce Planning: Companies can gain valuable insights into the availability of talent across Africa, assisting with decisions related to market expansion, office locations, and talent acquisition. Techsalerator’s Job Openings Data in Africa is a critical resource for understanding the diverse and evolving job markets across the continent. By providing up-to-date and detailed information on job postings, it supports effective decision-making for businesses, job seekers, and labor market analysts.

Techsalerator’s Job Openings Data in Oceania provides a detailed and comprehensive dataset designed to offer businesses, recruiters, labor market analysts, and job seekers a clear view of employment opportunities across the Oceania region. This dataset aggregates job postings from a diverse range of sources on a daily basis, ensuring users have access to the most current and extensive collection of job openings available in Oceania.

Key Features of the Dataset: Broad Coverage:

The dataset consolidates job postings from a variety of sources including company career pages, job boards, recruitment agencies, and professional networking platforms. This extensive coverage ensures that users receive a wide array of job opportunities from multiple channels. Daily Updates:

Job posting data is updated daily, providing users with real-time insights into the job market. This frequent updating ensures that the information is current and reflects the latest job openings and market conditions. Sector-Specific Data:

Job postings are categorized by industry sectors such as technology, healthcare, finance, education, hospitality, and more. This segmentation allows users to analyze trends and opportunities within specific sectors. Regional Breakdown:

The dataset includes detailed information on job openings across various countries and territories within Oceania. This regional breakdown helps users understand job market dynamics and opportunities in different geographic locations. Role and Skill Insights:

The dataset provides information on job roles, required skills, qualifications, and experience levels. This feature helps job seekers find opportunities that match their expertise and aids recruiters in identifying candidates with the desired skill sets. Company Information:

Users can access details about the companies posting job openings, including company names, industries, and locations. This data is useful for understanding which companies are hiring and where the demand for talent is high. Historical Data:

The dataset may include historical job posting data, enabling users to analyze trends and changes in the job market over time. This feature supports trend analysis and longitudinal studies. Oceania Countries and Territories Covered: Countries: Australia Fiji Kiribati Marshall Islands Micronesia (Federated States of) Nauru New Zealand Palau Papua New Guinea Samoa Solomon Islands Tonga Tuvalu Vanuatu Territories: American Samoa (U.S. territory) French Polynesia (French overseas collectivity) Guam (U.S. territory) New Caledonia (French special collectivity) Northern Mariana Islands (U.S. territory) Wallis and Futuna (French overseas collectivity) Benefits of the Dataset: Effective Recruitment: Recruiters and HR professionals can use the dataset to identify hiring trends, understand competitive hiring practices, and refine recruitment strategies based on real-time market insights. Labor Market Analysis: Analysts and policymakers can leverage the dataset to study employment trends, identify skill gaps, and evaluate job market opportunities across different regions and sectors. Job Seeker Support: Job seekers can access a comprehensive and updated list of job openings tailored to their skills and preferred locations, improving the efficiency and effectiveness of their job search. Workforce Planning: Companies can gain valuable insights into the availability of talent in various countries and territories, assisting with strategic decisions related to market expansion and talent acquisition. Techsalerator’s Job Openings Data in Oceania is a crucial resource for understanding the diverse job markets across the region. By providing up-to-date and detailed information on job postings, it supports informed decision-making for businesses, job seekers, and labor market analysts.

Techsalerator’s Job Openings Data in Europe is a robust and meticulously curated dataset designed to provide businesses, recruiters, labor market analysts, and job seekers with a comprehensive view of employment opportunities across the continent. This dataset aggregates job postings from a wide range of sources on a daily basis, ensuring that users have access to the most current and extensive collection of job openings available in Europe.

Key Features of the Dataset: Comprehensive Coverage:

The dataset captures job postings from numerous sources, including company career pages, job boards, recruitment agencies, and professional networking sites. This broad coverage ensures that the dataset includes job opportunities across various platforms and channels. Daily Aggregation:

Data is updated daily, providing users with real-time insights into the job market. This frequent updating ensures that the information is current and reflects the latest trends and changes in job availability. Sector-Specific Insights:

Job postings are categorized by industry sectors such as technology, healthcare, finance, education, manufacturing, and more. This categorization helps users analyze job market trends specific to different sectors and industries. Regional Breakdown:

The dataset includes detailed information on job openings across different regions and cities in Europe. This regional breakdown allows users to understand job market dynamics and opportunities in various geographic locations. Role and Skill Analysis:

Data includes information on job roles, required skills, qualifications, and experience levels. This helps job seekers identify opportunities that match their expertise and assists recruiters in finding candidates with the right skill sets. Company Insights:

Users can access data on the companies posting job openings, including company names, industries, and locations. This information is useful for understanding which companies are hiring and where the demand for talent is concentrated. Historical Data:

The dataset may include historical job posting data, enabling trend analysis and comparative studies over time. This feature allows users to track changes in job market demand and employment trends. EU Countries Covered: Austria Belgium Bulgaria Croatia Cyprus Czech Republic Denmark Estonia Finland France Germany Greece Hungary Ireland Italy Latvia Lithuania Luxembourg Malta Netherlands Poland Portugal Romania Slovakia Slovenia Spain Sweden Benefits of the Dataset: Enhanced Recruitment Strategies: Recruiters and HR professionals can use the dataset to identify trends in job postings, understand competitive hiring practices, and optimize their recruitment strategies based on current market conditions. Labor Market Analysis: Analysts and policymakers can leverage the data to study labor market trends, identify skill gaps, and evaluate employment opportunities across different regions and sectors. Job Seeker Support: Job seekers can access a comprehensive list of job openings, tailored to their skills and preferred locations, facilitating a more efficient and targeted job search process. Strategic Workforce Planning: Companies can gain insights into the availability of talent in various regions, helping them make informed decisions about expanding operations or setting up new offices. Techsalerator’s Job Openings Data in Europe provides a crucial resource for understanding the dynamic European job market. By offering detailed, up-to-date information on job postings across multiple sectors and regions, it supports effective decision-making for businesses, job seekers, and market analysts alike.

📊 Google Data for Market Intelligence, Business Validation & Lead Enrichment Google Data is one of the most valuable sources of location-based business intelligence available today. At Canaria, we’ve built a robust, scalable system for extracting, enriching, and delivering verified business data from Google Maps—turning raw location profiles into high-resolution, actionable insights.

Our Google Maps Company Profile Data includes structured metadata on businesses across the U.S., such as company names, standardized addresses, geographic coordinates, phone numbers, websites, business categories, open hours, diversity and ownership tags, star ratings, and detailed review distributions. Whether you're modeling a market, identifying leads, enriching a CRM, or evaluating risk, our Google Data gives your team an accurate, up-to-date view of business activity at the local level.

This dataset is updated weekly, and is fully customizable—allowing you to pull exactly what you need, whether you're targeting a specific geography, industry segment, review range, or open-hour window.

🌎 What Makes Canaria’s Google Data Unique? • Location Precision – Every business record is enriched with latitude/longitude, ZIP code, and Google Plus Code to ensure exact geolocation • Reputation Signals – Review tags, star ratings, and review counts are included to allow brand sentiment scoring and risk monitoring • Diversity & Ownership Tags – Capture public-facing declarations such as “women-owned” or “Asian-owned” for DEI, ESG, and compliance applications • Contact Readiness – Clean, standardized phone numbers and domains help teams route leads to sales, support, or customer success • Operational Visibility – Up-to-date open hours, categories, and branch information help validate which locations are active and when

Our data is built to be matched, integrated, and analyzed—and is trusted by clients in financial services, go-to-market strategy, HR tech, and analytics platforms.

🧠 What This Google Data Solves Canaria Google Data answers critical operational, market, and GTM questions like:

• Which businesses are actively operating in my target region or category? • Which leads are real, verified, and tied to an actual physical branch? • How can I detect underperforming companies based on review sentiment? • Where should I expand, prospect, or invest based on geographic presence? • How can I enhance my CRM, enrichment model, or targeting strategy using location-based data?

✅ Key Use Cases for Google Maps Business Data Our clients leverage Google Data across a wide spectrum of industries and functions. Here are the top use cases:

🔍 Lead Scoring & Business Validation • Confirm the legitimacy and physical presence of potential customers, partners, or competitors using verified Google Data • Rank leads based on proximity, star ratings, review volume, or completeness of listing • Filter spammy or low-quality leads using negative review keywords and tag summaries • Validate ABM targets before outreach using enriched business details like phone, website, and hours

📍 Location Intelligence & Market Mapping • Visualize company distributions across geographies using Google Maps coordinates and ZIPs • Understand market saturation, density, and white space across business categories • Identify underserved ZIP codes or local business deserts • Track presence and expansion across regional clusters and industry corridors

⚠️ Company Risk & Brand Reputation Scoring • Monitor Google Maps reviews for sentiment signals such as “scam”, “spam”, “calls”, or service complaints • Detect risk-prone or underperforming locations using star rating distributions and review counts • Evaluate consistency of open hours, contact numbers, and categories for signs of listing accuracy or abandonment • Integrate risk flags into investment models, KYC/KYB platforms, or internal alerting systems

🗃️ CRM & RevOps Enrichment • Enrich CRM or lead databases with phone numbers, web domains, physical addresses, and geolocation from Google Data • Use business category classification for segmentation and routing • Detect duplicates or outdated data by matching your records with the most current Google listing • Enable advanced workflows like field-based rep routing, localized campaign assignment, or automated ABM triggers

📈 Business Intelligence & Strategic Planning • Build dashboards powered by Google Maps data, including business counts, category distributions, and review activity • Overlay business presence with population, workforce, or customer base for location planning • Benchmark performance across cities, regions, or market verticals • Track mobility and change by comparing past and current Google Maps metadata

💼 DEI, ESG & Ownership Profiling • Identify minority-owned, women-owned, or other diversity-flagged companies using Google Data ownership attributes • Build datasets aligned with supplier diversity mandates or ESG investment strategies • Segment location insi...

PredictLeads offers a robust data solution specifically tailored for venture capital and private equity firms, delivering critical insights into the financing landscape. Our platform provides B2B intent data and company funding data to help investors identify early-stage growth signals, discover promising startups, and monitor industry trends.

With VC funding data, investors gain access to comprehensive details on companies backed by venture capital, spanning various funding stages. Our alternative data offers unique insights into emerging market trends, allowing firms to enhance their investment strategies. Investor data further supports firms by revealing competitor movements, enabling co-investment opportunities, and deepening insight into investor networks.

Key Features of PredictLeads Financing Events Data:

➡️ Comprehensive Company Funding Data: Access detailed insights on funding rounds, including investment amounts, types, and investors, to understand market opportunities. ➡️ Real-Time and Historical Funding Insights: Leverage up-to-date and historical B2B intent data to track funding trends and optimize investment timing. ➡️ Competitor and Market Analysis: Combine B2B intent data with financing information for in-depth analysis of competitor activity and market shifts. ➡️ Web Scraping Data for Accuracy: Our data is sourced from over 152,000 reliable sources, ensuring timely and accurate information for investor analysis. ➡️ Enhanced Personalized Outreach: Target companies with recent investments, including VC and PE-backed firms, to develop effective, personalized engagement strategies.

PredictLeads delivers a comprehensive financing events dataset designed to help venture capital (VC) and private equity (PE) firms track funding rounds, investment trends, and emerging startups. By leveraging real-time and historical company funding data, investors can identify early-stage opportunities, analyze competitor moves, and optimize deal sourcing strategies.

Use Cases: ✅ Deal Tracking – Spot companies in active funding rounds to identify investment-ready startups. ✅ Market Research – Monitor sector growth, investor activity, and funding trends to stay ahead of the market. ✅ Competitor Analysis – Analyze funding events of competitors and portfolio companies to assess market positioning. ✅ Investor Outreach – Target VC and PE-backed companies for co-investment and partnership opportunities. ✅ CRM Enrichment – Integrate company funding data into CRM systems for personalized investment insights.

Key API Attributes: - id (string, UUID) – Unique identifier for the financing event. - effective_date (ISO 8601 date-time) – Date when the investment was made. - found_at (ISO 8601 date-time) – Timestamp of when the event was detected. - categories (array of strings) – Funding round types (e.g., "series_a", "venture"). - financing_type (string) – Type of funding event (e.g., "Series A", "Private Equity"). - amount (string) – Investment amount (e.g., "$50M"). - amount_normalized (integer) – Investment amount in numeric format (e.g., 50000000). - source_urls (array of URLs) – Links to articles confirming the funding event. - company (object) – The funded company, including its domain and company name. - investors (array of objects) – List of investors involved in the financing round.

📌 Used by top VC and PE firms to drive data-driven investment strategies and gain a competitive edge in deal sourcing.

PredictLeads Docs: https://docs.predictleads.com/v3/guide/financing_events_dataset

Success.ai offers a comprehensive, enterprise-ready B2B leads data solution, ideal for businesses seeking access to over 150 million verified employee profiles and 170 million work emails. Our data empowers organizations across industries to target key decision-makers, optimize recruitment, and fuel B2B marketing efforts. Whether you're looking for UK B2B data, B2B marketing data, or global B2B contact data, Success.ai provides the insights you need with pinpoint accuracy.

Tailored for B2B Sales, Marketing, Recruitment and more: Our B2B contact data and B2B email data solutions are designed to enhance your lead generation, sales, and recruitment efforts. Build hyper-targeted lists based on job title, industry, seniority, and geographic location. Whether you’re reaching mid-level professionals or C-suite executives, Success.ai delivers the data you need to connect with the right people.

Key Categories Served: B2B sales leads – Identify decision-makers in key industries, B2B marketing data – Target professionals for your marketing campaigns, Recruitment data – Source top talent efficiently and reduce hiring times, CRM enrichment – Update and enhance your CRM with verified, updated data, Global reach – Coverage across 195 countries, including the United States, United Kingdom, Germany, India, Singapore, and more.

Global Coverage with Real-Time Accuracy: Success.ai’s dataset spans a wide range of industries such as technology, finance, healthcare, and manufacturing. With continuous real-time updates, your team can rely on the most accurate data available: 150M+ Employee Profiles: Access professional profiles worldwide with insights including full name, job title, seniority, and industry. 170M Verified Work Emails: Reach decision-makers directly with verified work emails, available across industries and geographies, including Singapore and UK B2B data. GDPR-Compliant: Our data is fully compliant with GDPR and other global privacy regulations, ensuring safe and legal use of B2B marketing data.

Key Data Points for Every Employee Profile: Every profile in Success.ai’s database includes over 20 critical data points, providing the information needed to power B2B sales and marketing campaigns: Full Name, Job Title, Company, Work Email, Location, Phone Number, LinkedIn Profile, Experience, Education, Technographic Data, Languages, Certifications, Industry, Publications & Awards.

Use Cases Across Industries: Success.ai’s B2B data solution is incredibly versatile and can support various enterprise use cases, including: B2B Marketing Campaigns: Reach high-value professionals in industries such as technology, finance, and healthcare. Enterprise Sales Outreach: Build targeted B2B contact lists to improve sales efforts and increase conversions. Talent Acquisition: Accelerate hiring by sourcing top talent with accurate and updated employee data, filtered by job title, industry, and location. Market Research: Gain insights into employment trends and company profiles to enrich market research. CRM Data Enrichment: Ensure your CRM stays accurate by integrating updated B2B contact data. Event Targeting: Create lists for webinars, conferences, and product launches by targeting professionals in key industries.

Use Cases for Success.ai's Contact Data - Targeted B2B Marketing: Create precise campaigns by targeting key professionals in industries like tech and finance. - Sales Outreach: Build focused sales lists of decision-makers and C-suite executives for faster deal cycles. - Recruiting Top Talent: Easily find and hire qualified professionals with updated employee profiles. - CRM Enrichment: Keep your CRM current with verified, accurate employee data. - Event Targeting: Create attendee lists for events by targeting relevant professionals in key sectors. - Market Research: Gain insights into employment trends and company profiles for better business decisions. - Executive Search: Source senior executives and leaders for headhunting and recruitment. - Partnership Building: Find the right companies and key people to develop strategic partnerships.

Why Choose Success.ai’s Employee Data? Success.ai is the top choice for enterprises looking for comprehensive and affordable B2B data solutions. Here’s why: Unmatched Accuracy: Our AI-powered validation process ensures 99% accuracy across all data points, resulting in higher engagement and fewer bounces. Global Scale: With 150M+ employee profiles and 170M verified work emails, Success.ai provides extensive coverage for UK B2B data, B2B marketing data, and global contacts. Competitive Pricing: We offer the most competitive rates on the market, undercutting major competitors like Lusha, Cognism, and ZoomInfo. Tailored Solutions: Our white-glove service ensures we deliver exactly what you need, in the format that suits your workflow (CSV, Excel, etc.). Real-Time Updates: Our data is continuously updated, so you always have the latest information, unlike static da...