Company Datasets for valuable business insights!

Discover new business prospects, identify investment opportunities, track competitor performance, and streamline your sales efforts with comprehensive Company Datasets.

These datasets are sourced from top industry providers, ensuring you have access to high-quality information:

• Owler: Gain valuable business insights and competitive intelligence. -AngelList: Receive fresh startup data transformed into actionable insights. -CrunchBase: Access clean, parsed, and ready-to-use business data from private and public companies. -Craft.co: Make data-informed business decisions with Craft.co's company datasets. -Product Hunt: Harness the Product Hunt dataset, a leader in curating the best new products.

We provide fresh and ready-to-use company data, eliminating the need for complex scraping and parsing. Our data includes crucial details such as:

• Company name;
• Size;
• Founding date;
• Location;
• Industry;
• Revenue;
• Employee count;
• Competitors.

You can choose your preferred data delivery method, including various storage options, delivery frequency, and input/output formats.

Receive datasets in CSV, JSON, and other formats, with storage options like AWS S3 and Google Cloud Storage. Opt for one-time, monthly, quarterly, or bi-annual data delivery.

With Oxylabs Datasets, you can count on:

• Fresh and accurate data collected and parsed by our expert web scraping team.
• Time and resource savings, allowing you to focus on data analysis and achieving your business goals.
• A customized approach tailored to your specific business needs.
• Legal compliance in line with GDPR and CCPA standards, thanks to our membership in the Ethical Web Data Collection Initiative.

Pricing Options:

Standard Datasets: choose from various ready-to-use datasets with standardized data schemas, priced from $1,000/month.

Custom Datasets: Tailor datasets from any public web domain to your unique business needs. Contact our sales team for custom pricing.

Experience a seamless journey with Oxylabs:

• Understanding your data needs: We work closely to understand your business nature and daily operations, defining your unique data requirements.
• Developing a customized solution: Our experts create a custom framework to extract public data using our in-house web scraping infrastructure.
• Delivering data sample: We provide a sample for your feedback on data quality and the entire delivery process.
• Continuous data delivery: We continuously collect public data and deliver custom datasets per the agreed frequency.

Unlock the power of data with Oxylabs' Company Datasets and supercharge your business insights today!

Use our Best Buy products to collect ratings, prices, and descriptions about products from an e-commerce online web. You can purchase either the entire dataset or a customized subset, depending on your requirements. The Best Buy Products Dataset stands as a comprehensive resource for businesses, researchers, and analysts aiming to navigate the vast array of products offered by Best Buy, a leading retailer in consumer electronics and technology. Tailored to provide a deep understanding of Best Buy's e-commerce ecosystem, this dataset facilitates market analysis, pricing optimization, customer behavior comprehension, and competitor assessment. At its core, the dataset encompasses essential attributes such as product ID, title, descriptions, ratings, reviews, pricing details, and seller information. These fundamental data elements empower users to glean insights into product performance, customer sentiment, and seller credibility, thereby facilitating informed decision-making processes. Whether you're a retailer looking to enhance your product portfolio, a researcher investigating trends in consumer electronics, or an analyst seeking to refine e-commerce strategies, the Best Buy Products Dataset offers a valuable resource for uncovering opportunities and driving success in the ever-evolving landscape of retail.

Description

The datasets demonstrate the malware economy and the value chain published in our paper, Malware Finances and Operations: a Data-Driven Study of the Value Chain for Infections and Compromised Access, at the 12th International Workshop on Cyber Crime (IWCC 2023), part of the ARES Conference, published by the International Conference Proceedings Series of the ACM ICPS.

Using the well-documented scripts, it is straightforward to reproduce our findings. It takes an estimated 1 hour of human time and 3 hours of computing time to duplicate our key findings from MalwareInfectionSet; around one hour with VictimAccessSet; and minutes to replicate the price calculations using AccountAccessSet. See the included README.md files and Python scripts.

We choose to represent each victim by a single JavaScript Object Notation (JSON) data file. Data sources provide sets of victim JSON data files from which we've extracted the essential information and omitted Personally Identifiable Information (PII). We collected, curated, and modelled three datasets, which we publish under the Creative Commons Attribution 4.0 International License.

1. MalwareInfectionSet
We discover (and, to the best of our knowledge, document scientifically for the first time) that malware networks appear to dump their data collections online. We collected these infostealer malware logs available for free. We utilise 245 malware log dumps from 2019 and 2020 originating from 14 malware networks. The dataset contains 1.8 million victim files, with a dataset size of 15 GB.

2. VictimAccessSet
We demonstrate how Infostealer malware networks sell access to infected victims. Genesis Market focuses on user-friendliness and continuous supply of compromised data. Marketplace listings include everything necessary to gain access to the victim's online accounts, including passwords and usernames, but also detailed collection of information which provides a clone of the victim's browser session. Indeed, Genesis Market simplifies the import of compromised victim authentication data into a web browser session. We measure the prices on Genesis Market and how compromised device prices are determined. We crawled the website between April 2019 and May 2022, collecting the web pages offering the resources for sale. The dataset contains 0.5 million victim files, with a dataset size of 3.5 GB.

3. AccountAccessSet
The Database marketplace operates inside the anonymous Tor network. Vendors offer their goods for sale, and customers can purchase them with Bitcoins. The marketplace sells online accounts, such as PayPal and Spotify, as well as private datasets, such as driver's licence photographs and tax forms. We then collect data from Database Market, where vendors sell online credentials, and investigate similarly. To build our dataset, we crawled the website between November 2021 and June 2022, collecting the web pages offering the credentials for sale. The dataset contains 33,896 victim files, with a dataset size of 400 MB.

Credits Authors

• Billy Bob Brumley (Tampere University, Tampere, Finland)
• Juha Nurmi (Tampere University, Tampere, Finland)
• Mikko Niemelä (Cyber Intelligence House, Singapore)

Funding

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under project numbers 804476 (SCARE) and 952622 (SPIRS).

Alternative links to download: AccountAccessSet, MalwareInfectionSet, and VictimAccessSet.

This dataset contains a list of sales and movement data by item and department appended monthly. Update Frequency : Monthly

Wirestock's AI/ML Image Training Data, 4.5M Files with Metadata: This data product is a unique offering in the realm of AI/ML training data. What sets it apart is the sheer volume and diversity of the dataset, which includes 4.5 million files spanning across 20 different categories. These categories range from Animals/Wildlife and The Arts to Technology and Transportation, providing a rich and varied dataset for AI/ML applications.

The data is sourced from Wirestock's platform, where creators upload and sell their photos, videos, and AI art online. This means that the data is not only vast but also constantly updated, ensuring a fresh and relevant dataset for your AI/ML needs. The data is collected in a GDPR-compliant manner, ensuring the privacy and rights of the creators are respected.

The primary use-cases for this data product are numerous. It is ideal for training machine learning models for image recognition, improving computer vision algorithms, and enhancing AI applications in various industries such as retail, healthcare, and transportation. The diversity of the dataset also means it can be used for more niche applications, such as training AI to recognize specific objects or scenes.

This data product fits into Wirestock's broader data offering as a key resource for AI/ML training. Wirestock is a platform for creators to sell their work, and this dataset is a collection of that work. It represents the breadth and depth of content available on Wirestock, making it a valuable resource for any company working with AI/ML.

The core benefits of this dataset are its volume, diversity, and quality. With 4.5 million files, it provides a vast resource for AI training. The diversity of the dataset, spanning 20 categories, ensures a wide range of images for training purposes. The quality of the images is also high, as they are sourced from creators selling their work on Wirestock.

In terms of how the data is collected, creators upload their work to Wirestock, where it is then sold on various marketplaces. This means the data is sourced directly from creators, ensuring a diverse and unique dataset. The data includes both the images themselves and associated metadata, providing additional context for each image.

The different image categories included in this dataset are Animals/Wildlife, The Arts, Backgrounds/Textures, Beauty/Fashion, Buildings/Landmarks, Business/Finance, Celebrities, Education, Emotions, Food Drinks, Holidays, Industrial, Interiors, Nature Parks/Outdoor, People, Religion, Science, Signs/Symbols, Sports/Recreation, Technology, Transportation, Vintage, Healthcare/Medical, Objects, and Miscellaneous. This wide range of categories ensures a diverse dataset that can cater to a variety of AI/ML applications.

Use our Instagram dataset (public data) to extract business and non-business information from complete public profiles and filter by hashtags, followers, account type, or engagement score. Depending on your needs, you may purchase the entire dataset or a customized subset. Popular use cases include sentiment analysis, brand monitoring, influencer marketing, and more. The dataset includes all major data points: # of followers, verified status, account type (business / non-business), links, posts, comments, location, engagement score, hashtags, and much more.

Dataset Card for "sales-conversations"

This dataset was created for the purpose of training a sales agent chatbot that can convince people. The initial idea came from: textbooks is all you need https://arxiv.org/abs/2306.11644 gpt-3.5-turbo was used for the generation

  Structure

The conversations have a customer and a salesman which appear always in changing order. customer, salesman, customer, salesman, etc. The customer always starts the conversation Who ends… See the full description on the dataset page: https://huggingface.co/datasets/goendalf666/sales-conversations.

Unlock the full potential of LinkedIn data with our extensive dataset that combines profiles, company information, and job listings into one powerful resource for business decision-making, strategic hiring, competitive analysis, and market trend insights. This all-encompassing dataset is ideal for professionals, recruiters, analysts, and marketers aiming to enhance their strategies and operations across various business functions. Dataset Features

Profiles: Dive into detailed public profiles featuring names, titles, positions, experience, education, skills, and more. Utilize this data for talent sourcing, lead generation, and investment signaling, with a refresh rate ensuring up to 30 million records per month. Companies: Access comprehensive company data including ID, country, industry, size, number of followers, website details, subsidiaries, and posts. Tailored subsets by industry or region provide invaluable insights for CRM enrichment, competitive intelligence, and understanding the startup ecosystem, updated monthly with up to 40 million records. Job Listings: Explore current job opportunities detailed with job titles, company names, locations, and employment specifics such as seniority levels and employment functions. This dataset includes direct application links and real-time application numbers, serving as a crucial tool for job seekers and analysts looking to understand industry trends and the job market dynamics.

Customizable Subsets for Specific Needs Our LinkedIn dataset offers the flexibility to tailor the dataset according to your specific business requirements. Whether you need comprehensive insights across all data points or are focused on specific segments like job listings, company profiles, or individual professional details, we can customize the dataset to match your needs. This modular approach ensures that you get only the data that is most relevant to your objectives, maximizing efficiency and relevance in your strategic applications. Popular Use Cases

Strategic Hiring and Recruiting: Track talent movement, identify growth opportunities, and enhance your recruiting efforts with targeted data. Market Analysis and Competitive Intelligence: Gain a competitive edge by analyzing company growth, industry trends, and strategic opportunities. Lead Generation and CRM Enrichment: Enrich your database with up-to-date company and professional data for targeted marketing and sales strategies. Job Market Insights and Trends: Leverage detailed job listings for a nuanced understanding of employment trends and opportunities, facilitating effective job matching and market analysis. AI-Driven Predictive Analytics: Utilize AI algorithms to analyze large datasets for predicting industry shifts, optimizing business operations, and enhancing decision-making processes based on actionable data insights.

Whether you are mapping out competitive landscapes, sourcing new talent, or analyzing job market trends, our LinkedIn dataset provides the tools you need to succeed. Customize your access to fit specific needs, ensuring that you have the most relevant and timely data at your fingertips.

Index returns, market cap, constituent detail data from various index providers, all linked to S&P Global companies and securities.

Content

An Adidas sales dataset is a collection of data that includes information on the sales of Adidas products. This type of dataset may include details such as the number of units sold, the total sales revenue, the location of the sales, the type of product sold, and any other relevant information.

Adidas sales data can be useful for a variety of purposes, such as analyzing sales trends, identifying successful products or marketing campaigns, and developing strategies for future sales. It can also be used to compare Adidas sales to those of competitors, or to analyze the effectiveness of different marketing or sales channels.

There are a variety of sources that could potentially provide an Adidas sales dataset, including Adidas itself, market research firms, government agencies, or other organizations that track sales data. The specific data points included in an Adidas sales dataset may vary depending on the source and the purpose for which it is being used.

Dataset Glossary (Column-Wise) - Retailer : Represents the business or individual that sells Adidas products directly to consumers.

• Retailer ID : A unique identifier assigned to each retailer in the dataset.

• Invoice Date : The date when a particular invoice or sales transaction took place.

• Region : Refers to a specific geographical area or district where the sales activity or retail operations occur.

• State : Represents a specific administrative division or territory within a country.

• City : Refers to an urban area or municipality where the sales activity or retail operations are conducted.

• Product : Represents the classification or grouping of Adidas products.

• Price per Unit : The cost or price associated with a single unit of a product.

• Units Sold : The quantity or number of units of a particular product sold during a specific sales transaction.

• Total Sales : The overall revenue generated from the sales transactions.

• Operating Profit : The profit earned by the retailer from its normal business operations.

• Sales Method : The approach or channel used by the retailer to sell its products or services.

Our Market Analysis dataset uncovers consumer movement patterns across brands and categories, helping you define your true trade area and optimize location strategy.

Using foot traffic data tied to specific POIs, this GDPR-compliant, non-PII dataset highlights where your visitors also shop — enabling smarter site selection, lease renegotiation, and competitive market analysis.

Key data points include: - Cross-visitation trends by brand/category - Consumer reach and trade area definition - Weekly, monthly, and quarterly aggregations - Cleaned, normalized, and updated data - Non-PII and fully GDPR-compliant

Focused on the U.S. market, this dataset is ideal for retailers, landlords, and consultants looking to map behavior, refine market coverage, and drive informed decisions.

Represents the Direct Farm Markets in Middlesex County, NJ including Direct Markets and Tailgate Markets. Direct Markets include markets that are on or adjacent to farms that largely sell products produced on premises.Tailgate Markets, or farmer's markets are retail marketplaces that sell foods directly by farmers to consumers. This dataset includes information such as Farm or Farm Market Name, Address, Hours of Operation, Contact Phone Number, Contact Email Address, Contact Website URL, a general description of products sold, and other information. This dataset is for reference and some information is subject to change without notice.

Sales data for all Islanders Board Of Industry & Service (IBIS) stores.

These datasets contain reviews from the Steam video game platform, and information about which games were bundled together.

Metadata includes

• reviews

• purchases, plays, recommends (likes)

• product bundles

• pricing information

Basic Statistics:

• Reviews: 7,793,069

• Users: 2,567,538

• Items: 15,474

• Bundles: 615

Data Driven Detroit created the data by selecting locations from NETS and ESRI business data with proper NAICS codes, then adding and deleting though local knowledge and confirmation with Google Streetview. These locations are Grocery stores which primarily sell food and don't include convenience stores. Visual confirmation cues included the existence of the word "grocery" in the name, or the presence of shopping carts.

Autos include all passenger cars, including station wagons. The U.S. Bureau of Economic Analysis releases auto and truck sales data, which are used in the preparation of estimates of personal consumption expenditures.

This is USDA's Agricultural Marketing Service's list of wholesale markets, or facilities where wholesalers receive large quantities of commodities by rail, truck, and air from local growers as well as producers around the world for sale to grocers, restaurants, institutions, and other businesses. About 90% of wholesale markets sell fresh fruits and vegetables, but there are also seafood, meat, and flower wholesale markets.

According to Cognitive Market Research, the global Data Broker Services market size is USD 268154.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 8.00% from 2024 to 2031.

North America held the major market of more than 40% of the global revenue with a market size of USD 107261.68 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.2% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 80446.26 million.
Asia Pacific held the market of around 23% of the global revenue with a market size of USD 61675.47 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.0% from 2024 to 2031.
Latin America market of more than 5% of the global revenue with a market size of USD 13407.71 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.4% from 2024 to 2031.
Middle East and Africa held the major market ofaround 2% of the global revenue with a market size of USD 5363.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.7% from 2024 to 2031.
The Subscription Paid held the highest Data Broker Services market revenue share in 2024.

Market Dynamics of Data Broker Services Market

Key Drivers of Data Broker Services Market

Increasing Demand for Personalized Marketing Solutions to Increase the Demand Globally

The Data Broker Services Market is being driven by the increasing demand for personalized marketing solutions. Companies across various industries are leveraging data broker services to access valuable consumer insights and enhance their marketing strategies. Data brokers offer a wide range of data sets, including demographic, behavioral, and transactional data, which can be used to create targeted marketing campaigns. By utilizing data broker services, companies can tailor their marketing messages to specific consumer segments, leading to higher engagement and conversion rates. This trend is expected to continue driving the growth of the Data Broker Services Market as businesses increasingly prioritize personalized marketing approaches to remain competitive in the digital age.

Growing Focus on Data Monetization to Propel Market Growth

Another key driver of the Data Broker Services Market is the growing focus on data monetization. Organizations are realizing the value of their data assets and are looking for ways to monetize them. Data broker services enable companies to sell their data to third parties, such as marketers, researchers, and other businesses, generating additional revenue streams. This trend is particularly prevalent in industries with large amounts of consumer data, such as retail, finance, and healthcare. By monetizing their data, companies can unlock new revenue opportunities and offset the costs associated with data collection and management. As the demand for data-driven insights continues to grow, the Data Broker Services Market is expected to expand, driven by the increasing number of organizations looking to capitalize on their data assets.

Restraint Factors Of Data Broker Services Market

Regulatory Challenges and Data Privacy Concerns to Limit the Sales

One of the key restraints in the Data Broker Services Market is the increasing regulatory challenges and data privacy concerns. With the implementation of regulations such as the GDPR in Europe and the CCPA in California, data brokers are facing stricter requirements for data collection, processing, and sharing. Compliance with these regulations requires significant resources and can limit the ability of data brokers to collect and monetize data. Additionally, concerns about data privacy and security among consumers are leading to greater scrutiny of data broker practices, further complicating the operating environment for these companies. As regulatory pressures continue to increase, data brokers may face challenges in expanding their operations and maintaining profitability.

Impact of Covid-19 on the Data Broker Services Market

The COVID-19 pandemic has had a mixed impact on the Data Broker Services Market. On one hand, the increased reliance on digital technologies and online services during the pandemic has led to a surge in data generation, creating new opportunities for data brokers. Organizations are increasingly seeking to understand changing consumer behaviors and preferences in the digital space, ...

Retail Sales in the United States increased 0.20 percent in February of 2025 over the previous month. This dataset provides - U.S. December Retail Sales Increased More Than Forecast - actual values, historical data, forecast, chart, statistics, economic calendar and news.