Comprehensive dataset of 358 Database management companies in Brazil as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

LinkedIn companies use datasets to access public company data for machine learning, ecosystem mapping, and strategic decisions. Popular use cases include competitive analysis, CRM enrichment, and lead generation.

Use our LinkedIn Companies Information dataset to access comprehensive data on companies worldwide, including business size, industry, employee profiles, and corporate activity. This dataset provides key company insights, organizational structure, and competitive landscape, tailored for market researchers, HR professionals, business analysts, and recruiters.

Leverage the LinkedIn Companies dataset to track company growth, analyze industry trends, and refine your recruitment strategies. By understanding company dynamics and employee movements, you can optimize sourcing efforts, enhance business development opportunities, and gain a strategic edge in your market. Stay informed and make data-backed decisions with this essential resource for understanding global company ecosystems.

Dataset Features

• timestamp: Represents the date and time when the company data was collected.
• id: Unique identifier for each company in the dataset.
• company_id: Identifier linking the company to an external database or internal system.
• url: Website or URL for more information about the company.
• name: The name of the company.
• about: Brief description of the company.
• description: More detailed information about the company's operations and offerings.
• organization_type: Type of the organization (e.g., private, public).
• industries: List of industries the company operates in.
• followers: Number of followers on the company's platform.
• headquarters: Location of the company's headquarters.
• country_code: Code for the country where the company is located.
• country_codes_array: List of country codes associated with the company (may represent various locations or markets).
• locations: Locations where the company operates.
• get_directions_url: URL to get directions to the company's location(s).
• formatted_locations: Human-readable format of the company's locations.
• website: The official website of the company.
• website_simplified: A simplified version of the company's website URL.
• company_size: Number of employees or company size.
• employees_in_linkedin: Number of employees listed on LinkedIn.
• employees: URL of employees.
• specialties: List of the company’s specializations or services.
• updates: Recent updates or news related to the company.
• crunchbase_url: Link to the company’s profile on Crunchbase.
• founded: Year when the company was founded.
• funding: Information on funding rounds or financial data.
• investors: Investors who have funded the company.
• alumni: Notable alumni from the company.
• alumni_information: Details about the alumni, their roles, or achievements.
• stock_info: Stock market information for publicly traded companies.
• affiliated: Companies or organizations affiliated with the company.
• image: Image representing the company.
• logo: URL of the official logo of the company.
• slogan: Company’s slogan or tagline.
• similar: URL of companies similar to this one.

Distribution

• Data Volume: 56.51M rows and 35 columns.
• Structure: Tabular format (CSV, Excel).

Usage

This dataset is ideal for:
- Market Research: Identifying key trends and patterns across different industries and geographies.
- Business Development: Analyzing potential partners, competitors, or customers.
- Investment Analysis: Assessing investment potential based on company size, funding, and industries.
- Recruitment & Talent Analytics: Understanding the workforce size and specialties of various companies.

Coverage

• Geographic Coverage: Global, with company locations and headquarters spanning multiple countries.
• Time Range: Data likely covers both current and historical information about companies.
• Demographics: Focuses on company attributes rather than demographics, but may contain information about the company's workforce.

License

CUSTOM

Please review the respective licenses below:

1. Data Provider's License
   • Bright Data Master Service Agreement

Who Can Use It

• Data Scientists: For building models, conducting research, or enhancing machine learning algorithms with business data.
• Researchers: For academic analysis in fields like economics, business, or technology.
• Businesses: For analysis, competitive benchmarking, and strategic development.
• Investors: For identifying and evaluating potential investment opportunities.

Dataset Name Ideas

• Global Company Profile Database
• **Business Intellige

Computer vision is one of the fastest growing industries at the moment and there are a lot of opportunites associated with this industry. Whether you run a development shop, staffing agency or sales/marketing related business this list will help you find opportunities with computer vision companies.

Comprehensive dataset of 27 Database management companies in Greece as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Success.ai offers a cutting-edge solution for businesses and organizations seeking Company Financial Data on private and public companies. Our comprehensive database is meticulously crafted to provide verified profiles, including contact details for financial decision-makers such as CFOs, financial analysts, corporate treasurers, and other key stakeholders. This robust dataset is continuously updated and validated using AI technology to ensure accuracy and relevance, empowering businesses to make informed decisions and optimize their financial strategies.

Key Features of Success.ai's Company Financial Data:

Global Coverage: Access data from over 70 million businesses worldwide, including public and private companies across all major industries and regions. Our datasets span 250+ countries, offering extensive reach for your financial analysis and market research.

Detailed Financial Profiles: Gain insights into company financials, including revenue, profit margins, funding rounds, and operational costs. Profiles are enriched with key contact details, including work emails, phone numbers, and physical addresses, ensuring direct access to decision-makers.

Industry-Specific Data: Tailored datasets for sectors such as financial services, manufacturing, technology, healthcare, and energy, among others. Each dataset is customized to meet the unique needs of industry professionals and analysts.

Real-Time Accuracy: With continuous updates powered by AI-driven validation, our financial data maintains a 99% accuracy rate, ensuring you have access to the most reliable and up-to-date information available.

Compliance and Security: All data is collected and processed in strict adherence to global compliance standards, including GDPR, ensuring ethical and lawful usage.

Why Choose Success.ai for Company Financial Data?

Best Price Guarantee: We pride ourselves on offering the most competitive pricing in the industry, ensuring you receive unparalleled value for comprehensive financial data.

AI-Validated Accuracy: Our advanced AI algorithms meticulously verify every data point to ensure precision and reliability, helping you avoid costly errors in your financial decision-making.

Customized Data Solutions: Whether you need data for a specific region, industry, or type of business, we tailor our datasets to align perfectly with your requirements.

Scalable Data Access: From small startups to global enterprises, our platform caters to businesses of all sizes, delivering scalable solutions to suit your operational needs.

Comprehensive Use Cases for Financial Data:

1. Strategic Financial Planning:

Leverage our detailed financial profiles to create accurate budgets, forecasts, and strategic plans. Gain insights into competitors’ financial health and market positions to make data-driven decisions.

1. Mergers and Acquisitions (M&A):

Access key financial details and contact information to streamline your M&A processes. Identify potential acquisition targets or partners with verified profiles and financial data.

1. Investment Analysis:

Evaluate the financial performance of public and private companies for informed investment decisions. Use our data to identify growth opportunities and assess risk factors.

1. Lead Generation and Sales:

Enhance your sales outreach by targeting CFOs, financial analysts, and other decision-makers with verified contact details. Utilize accurate email and phone data to increase conversion rates.

1. Market Research:

Understand market trends and financial benchmarks with our industry-specific datasets. Use the data for competitive analysis, benchmarking, and identifying market gaps.

APIs to Power Your Financial Strategies:

Enrichment API: Integrate real-time updates into your systems with our Enrichment API. Keep your financial data accurate and current to drive dynamic decision-making and maintain a competitive edge.

Lead Generation API: Supercharge your lead generation efforts with access to verified contact details for key financial decision-makers. Perfect for personalized outreach and targeted campaigns.

Tailored Solutions for Industry Professionals:

Financial Services Firms: Gain detailed insights into revenue streams, funding rounds, and operational costs for competitor analysis and client acquisition.

Corporate Finance Teams: Enhance decision-making with precise data on industry trends and benchmarks.

Consulting Firms: Deliver informed recommendations to clients with access to detailed financial datasets and key stakeholder profiles.

Investment Firms: Identify potential investment opportunities with verified data on financial performance and market positioning.

What Sets Success.ai Apart?

Extensive Database: Access detailed financial data for 70M+ companies worldwide, including small businesses, startups, and large corporations.

Ethical Practices: Our data collection and processing methods are fully comp...

The Business Structure Database (BSD) contains a small number of variables for almost all business organisations in the UK. The BSD is derived primarily from the Inter-Departmental Business Register (IDBR), which is a live register of data collected by HM Revenue and Customs via VAT and Pay As You Earn (PAYE) records. The IDBR data are complimented with data from ONS business surveys. If a business is liable for VAT (turnover exceeds the VAT threshold) and/or has at least one member of staff registered for the PAYE tax collection system, then the business will appear on the IDBR (and hence in the BSD). In 2004 it was estimated that the businesses listed on the IDBR accounted for almost 99 per cent of economic activity in the UK. Only very small businesses, such as the self-employed were not found on the IDBR.

The IDBR is frequently updated, and contains confidential information that cannot be accessed by non-civil servants without special permission. However, the ONS Virtual Micro-data Laboratory (VML) created and developed the BSD, which is a 'snapshot' in time of the IDBR, in order to provide a version of the IDBR for research use, taking full account of changes in ownership and restructuring of businesses. The 'snapshot' is taken around April, and the captured point-in-time data are supplied to the VML by the following September. The reporting period is generally the financial year. For example, the 2000 BSD file is produced in September 2000, using data captured from the IDBR in April 2000. The data will reflect the financial year of April 1999 to March 2000. However, the ONS may, during this time, update the IDBR with data on companies from its own business surveys, such as the Annual Business Survey (SN 7451).

The data are divided into 'enterprises' and 'local units'. An enterprise is the overall business organisation. A local unit is a 'plant', such as a factory, shop, branch, etc. In some cases, an enterprise will only have one local unit, and in other cases (such as a bank or supermarket), an enterprise will own many local units.

For each company, data are available on employment, turnover, foreign ownership, and industrial activity based on Standard Industrial Classification (SIC)92, SIC 2003 or SIC 2007. Year of 'birth' (company start-up date) and 'death' (termination date) are also included, as well as postcodes for both enterprises and their local units. Previously only pseudo-anonymised postcodes were available but now all postcodes are real.

The ONS is continually developing the BSD, and so researchers are strongly recommended to read all documentation pertaining to this dataset before using the data.

Linking to Other Business Studies
These data contain IDBR reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

Latest Edition Information
For the sixteenth edition (March 2024), data files and a variable catalogue document for 2023 have been added.

These data were generated as part of a two-and-a-half-year ESRC-funded research project examining the digitalisation of higher education (HE) and the educational technology (Edtech) industry in HE. Building on a theoretical lens of assetisation, it focused on forms of value in the sector, and governance challenges of digital data. It followed three groups of actors: UK universities, Edtech companies, and investors in Edtech. The researchers first sought to develop an overview of the Edtech industry in HE by building three databases on Edtech companies, investors in Edtech, and investment deals, using data downloaded from Crunchbase, a proprietary platform. Due to Crunchbase’s Terms of Service, only parts of one database are allowed to be submitted to this repository, i.e. a list of companies with the project’s classification. A report offering descriptive analysis of all three databases was produced and is submitted as well. A qualitative discursive analysis was conducted by analysing seven documents in depth. In the second phase, researchers conducted interviews with participants representing three groups of actors (n=43) and collected documents on their organisations. Moreover, a list of documents collected from Big Tech (Microsoft, Amazon, and Salesforce) were collected to contextualise the role of global digital infrastructure in HE. Due to commercial sensitivity, only lists of documents collected about investors and Big Tech are submitted to the repository. Researchers then conducted focus groups (n=6) with representatives of universities (n=19). The dataset includes transcripts of focus groups and outputs of writing by participants during the focus group. Finally, a public consultation was held via a survey, and 15 participants offered qualitative answers.

Comprehensive dataset of 2 Database management companies in Province of Cosenza, Italy as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

This list has data of about 3000+ companies specializing in computer vision from Enterprises and Startups to Studios. The information includes:

Location Company Name Linkedin profiles of key people Company Name No of employees Company Name LinkedIn profile Company Name List of key people Company Name Fund raised

This list is suitable for:

Agencies & service providers Pitch your services whether it be marketing, design or web development services.

Freelancers & developers Up your job hunting, contract work and gig opportunities search.

Product companies Companies with a product or service for computer vision companies.

Staffing and recruiting agencies Companies with a product or service for computer vision companies.

India Number of Registered Company data was reported at 1,171,230.000 Unit in 2018. This records a decrease from the previous number of 1,172,583.000 Unit for 2017. India Number of Registered Company data is updated yearly, averaging 152,036.000 Unit from Mar 1957 (Median) to 2018, with 62 observations. The data reached an all-time high of 1,172,583.000 Unit in 2017 and a record low of 26,682.000 Unit in 1962. India Number of Registered Company data remains active status in CEIC and is reported by Ministry of Corporate Affairs. The data is categorized under Global Database’s India – Table IN.OC001: Registered Company: At Work.

Database Platform as a Service Market Outlook

The Database Platform as a Service (DBPaaS) market is poised for substantial growth, with a market size that was valued at USD 9.5 billion in 2023 and is projected to reach USD 25.3 billion by 2032, growing at a compound annual growth rate (CAGR) of 11.5% during the forecast period. This remarkable growth is driven by factors such as the increasing adoption of cloud-based solutions, the surge in data generation across various sectors, and the need for scalable and efficient database management systems. Furthermore, the growing demand for real-time data analytics to derive actionable insights and the rising trend of digital transformation across industries are further propelling the market's expansion.

One of the critical growth drivers of the DBPaaS market is the widespread embrace of cloud technology across businesses of all sizes. As organizations increasingly migrate their operations to the cloud, the demand for flexible and cost-effective database management solutions has surged. DBPaaS allows companies to manage databases without the need for complex on-premises infrastructure, enabling them to focus more on their core business objectives. This cloud-first approach is particularly appealing to small and medium enterprises (SMEs) that may lack the resources to maintain robust IT infrastructures, thereby fueling market growth across this segment.

Moreover, the acceleration of digital transformation initiatives across various industries is another pivotal factor influencing the growth of the DBPaaS market. Industries such as BFSI, healthcare, IT and telecommunications, and retail are increasingly relying on digital solutions to optimize their operations, improve customer experiences, and gain competitive advantages. As these sectors generate vast amounts of data, the need for efficient and scalable database management systems becomes paramount. DBPaaS offers these industries the agility and scalability required to handle their data needs effectively, thereby contributing significantly to market expansion.

The ongoing advancements in real-time data analytics and the increasing importance of data-driven decision-making are also boosting the DBPaaS market. Organizations today are keen on leveraging big data and analytics to enhance business operations and customer satisfaction. DBPaaS solutions provide the necessary infrastructure and tools to manage and analyze large datasets efficiently, allowing businesses to derive insights that can drive strategic initiatives. The ability to access real-time data analytics is crucial for industries like retail and BFSI, where timely decisions can significantly impact performance and profitability.

As the DBPaaS market continues to evolve, the concept of a Database Private Cloud is gaining traction among organizations seeking enhanced security and control over their data. Unlike public cloud solutions, a Database Private Cloud offers dedicated resources and infrastructure, ensuring higher levels of data privacy and compliance with industry regulations. This model is particularly appealing to sectors such as healthcare and BFSI, where data sensitivity and confidentiality are paramount. By opting for a Database Private Cloud, businesses can maintain greater oversight of their data environments, tailoring their database management strategies to meet specific security and operational requirements. This approach not only enhances data protection but also allows for more customized and efficient database solutions, aligning with the growing demand for secure cloud-based services.

Regionally, North America dominates the DBPaaS market due to the early adoption of innovative technologies and the presence of major cloud service providers. The region's mature IT infrastructure, coupled with a strong focus on digital transformation across verticals, creates a conducive environment for DBPaaS growth. Meanwhile, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. Factors such as increasing investments in cloud infrastructure, rapid economic development, and the rising uptake of cloud services by SMEs in countries like India and China contribute to this regional surge. Europe also demonstrates steady growth, driven by stringent data protection regulations that encourage cloud adoption and database management solutions.

Service Type Analysis

The DBPaaS market is segmented based on service types into managed services and pr

Leverage high-quality B2B data with 468 enriched attributes, covering firmographics, financial stability, and industry classifications. Our AI-optimized dataset ensures accuracy through advanced deduplication and continuous updates. With 30+ years of expertise and 1,100+ trusted sources, we provide fully compliant, structured business data to power lead generation, risk assessment, CRM enrichment, market research, and more.

Key use cases of B2B Data have helped our customers in several areas :

1. Boost Lead Generation & Sales Outreach : Target the right businesses with precise, segmented contact lists for cold calling, email marketing, and industry-specific campaigns.
2. Enhance CRM & Web Data for Smarter Engagement : Enrich CRM records with instant access to detailed company profiles, visitor identification, and continuous data updates.
3. Strengthen Risk Assessment & Fraud Prevention : Evaluate supplier reliability, assess credit risk, and prevent fraud with deep firmographic and financial insights.
4. Gain a Competitive Edge with Market Research : Analyse industry trends, benchmark competitors, and identify automation-ready sectors for strategic positioning.
5. Optimize B2B Strategies with AI-Powered Insights : Leverage structured, compliant data to drive smarter business decisions across sales, marketing, and operations.

People data provides complete people information and gives the ability to link individual information to organizations and roles.

Every single contact from our firmographic database with 341 million+ companies comes directly from local sources that you can trust and are GDPR proof. We can deliver 200 firmographics such as company size, industry, legal status, revenue, employee size, opening hours, geocodes, import / export. BoldData is the nr.1 supplier of firmographic data supplier because we make use of thousands of local data sources. Ask us for a quote!

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.

Be one of the first companies to benefit from telephone verified contact data for a record that has just been added to our dataset within the last 24 hours. You will still receive all of the usual data fields that Market Location can offer.

Comprehensive dataset of 111,788 Construction companies in United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The Co-Creation Database groups scientific references on co-creation.

It mainly contains the title, abstract, DOI, and authors.

Two versions are available:

• Version 1.5 includes 13,501 references, from PubMed, ProQuest and CINAHL, from January 1970 to November 2021. Available in RIS (Research Information Systems) format and CSV (CSV UTF-8). Quality metrics: 9.38% false negatives; 20.35% false positives.
• Version 2.0 is an update from a classification model trained with version 1.5. It includes references from Scopus and Web of Science from January 1970 to March 2023, with an update of the previous databases used for version 1.5 from December 2021 to March 2023. Two CSV (CSV UTF-8) files are available. The "Co-Creation Database v2.0 - full.csv" combines the last version, 1.5 and the update, with 52,821 references. The file "Co-Creation Database v2.0 - adding.csv" has only the update, with 39,219 references. Quality metrics: 13.98% false negatives; 36.43% false positives.

To perform your search: we recommend you extend your search to the title and abstract since some data are initially missing. The RIS file can be uploaded to any references manager (e.g., Zotero, Mendeley, etc.), where you will have the feature to search. For example, here is the link for advanced search instructions in Zotero: https://www.zotero.org/support/searching. Additionally, You can run a Boolean search for CSV files using a Python script.

To improve the database in further updates: we make available an online form to submit any irrelevant references you may find or to submit any relevant reference not inside the last version. The form is available at the following link: https://forms.office.com/e/6vu9X0kBcw

It was produced as part of Health CASCADE, a Marie Skłodowska-Curie Innovative Training Network funded by the European Union's Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement n° 956501.

The work is made available under the terms of the license CC-BY-NC-4.0 (Creative Common Attribution - NonCommercial - NoDerivatives 4.0 International).

The Consumer Complaint Database is a collection of complaints about consumer financial products and services that we sent to companies for response. Complaints are published after the company responds, confirming a commercial relationship with the consumer, or after 15 days, whichever comes first. Complaints referred to other regulators, such as complaints about depository institutions with less than $10 billion in assets, are not published in the Consumer Complaint Database. The database generally updates daily.

France FR: Number of Listed Domestic Companies: Total data was reported at 465.000 Unit in 2017. This records a decrease from the previous number of 485.000 Unit for 2016. France FR: Number of Listed Domestic Companies: Total data is updated yearly, averaging 630.000 Unit from Dec 1975 (Median) to 2017, with 43 observations. The data reached an all-time high of 1,185.000 Unit in 2000 and a record low of 218.000 Unit in 1994. France FR: Number of Listed Domestic Companies: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s France – Table FR.World Bank.WDI: Financial Sector. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.