Listing of all active businesses currently registered with the Office of Finance. An "active" business is defined as a registered business whose owner has not notified the Office of Finance of a cease of business operations. Update Interval: Monthly. NAICS Codes are from 2007 NAICS: https://www.census.gov/cgi-bin/sssd/naics/naicsrch?chart=2007

Only counties in nonmetropolitan areas may be eligible for HUBZone designated status. In order for a nonmetropolitan county to qualify: the median household income in the county must be less than 80% of the nonmetropolitan state median household income, or the unemployment rate in the county must be at least 140% of either the national or state unemployment rate, or the county is classified as a Difficult Development Area, as designated by HUD within Alaska, Hawaii, or any territory or possession of the United States, outside of the 48 contiguous states.

The list tracks the number of businesses that NYC Business Acceleration has assisted in opening and how many jobs were created by those businesses. This data is up to date as of the date reflected in the "About" tab of this dataset.

Point of Interest (POI) is defined as an entity (such as a business) at a ground location (point) which may be (of interest). We provide high-quality POI data that is fresh, consistent, customizable, easy to use and with high-density coverage for all countries of the world.

This is our process flow:

Our machine learning systems continuously crawl for new POI data
Our geoparsing and geocoding calculates their geo locations
Our categorization systems cleanup and standardize the datasets
Our data pipeline API publishes the datasets on our data store

A new POI comes into existence. It could be a bar, a stadium, a museum, a restaurant, a cinema, or store, etc.. In today's interconnected world its information will appear very quickly in social media, pictures, websites, press releases. Soon after that, our systems will pick it up.

POI Data is in constant flux. Every minute worldwide over 200 businesses will move, over 600 new businesses will open their doors and over 400 businesses will cease to exist. And over 94% of all businesses have a public online presence of some kind tracking such changes. When a business changes, their website and social media presence will change too. We'll then extract and merge the new information, thus creating the most accurate and up-to-date business information dataset across the globe.

We offer our customers perpetual data licenses for any dataset representing this ever changing information, downloaded at any given point in time. This makes our company's licensing model unique in the current Data as a Service - DaaS Industry. Our customers don't have to delete our data after the expiration of a certain "Term", regardless of whether the data was purchased as a one time snapshot, or via our data update pipeline.

Customers requiring regularly updated datasets may subscribe to our Annual subscription plans. Our data is continuously being refreshed, therefore subscription plans are recommended for those who need the most up to date data. The main differentiators between us vs the competition are our flexible licensing terms and our data freshness.

Data samples may be downloaded at https://store.poidata.xyz/us

In a 2024 survey of small business leaders and IT professionals in the United States, 58 percent of respondents stated that employee data was their most compromised company data in cyberattacks. Additionally, 53 percent of respondents reported customer or consumer data as the second most impacted company data.

United States - Total Business Sales was 1733841.00000 Mil. of $ in February of 2025, according to the United States Federal Reserve. Historically, United States - Total Business Sales reached a record high of 1974148.00000 in December of 2024 and a record low of 478951.00000 in January of 1992. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Total Business Sales - last updated from the United States Federal Reserve on July of 2025.

NFIB Business Optimism Index in the United States decreased to 98.60 points in June from 98.80 points in May of 2025. This dataset provides - United States Nfib Business Optimism Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

A survey conducted from April to May 2022 found that six in 10 organizations in the United States designated an internal project manager or owner to manage compliance with state-level privacy laws. Around half of the organizations conducted data mapping and had an understanding of data practices across the organization. A further 41 percent said they updated privacy policies, while 40 percent said they were in the process of doing so.

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!

The Small Business Administration maintains the Dynamic Small Business Search (DSBS) database. As a small business registers in the System for Award Management, there is an opportunity to fill out the small business profile. The information provided populates DSBS. DSBS is another tool contracting officers use to identify potential small business contractors for upcoming contracting opportunities. Small businesses can also use DSBS to identify other small businesses for teaming and joint venturing.

Graph and download economic data for Number of Business Failures for United States (M09028USM474NNBR) from Jan 1893 to Jan 1933 about failures, business, and USA.

Access B2B Contact Data for North American Small Business Owners with Success.ai—your go-to provider for verified, high-quality business datasets. This dataset is tailored for businesses, agencies, and professionals seeking direct access to decision-makers within the small business ecosystem across North America. With over 170 million professional profiles, it’s an unparalleled resource for powering your marketing, sales, and lead generation efforts.

Key Features of the Dataset:

Verified Contact Details

Includes accurate and up-to-date email addresses and phone numbers to ensure you reach your targets reliably.

AI-validated for 99% accuracy, eliminating errors and reducing wasted efforts.

Detailed Professional Insights

Comprehensive data points include job titles, skills, work experience, and education to enable precise segmentation and targeting.

Enriched with insights into decision-making roles, helping you connect directly with small business owners, CEOs, and other key stakeholders.

Business-Specific Information

Covers essential details such as industry, company size, location, and more, enabling you to tailor your campaigns effectively. Ideal for profiling and understanding the unique needs of small businesses.

Continuously Updated Data

Our dataset is maintained and updated regularly to ensure relevance and accuracy in fast-changing market conditions. New business contacts are added frequently, helping you stay ahead of the competition.

Why Choose Success.ai?

At Success.ai, we understand the critical importance of high-quality data for your business success. Here’s why our dataset stands out:

Tailored for Small Business Engagement Focused specifically on North American small business owners, this dataset is an invaluable resource for building relationships with SMEs (Small and Medium Enterprises). Whether you’re targeting startups, local businesses, or established small enterprises, our dataset has you covered.

Comprehensive Coverage Across North America Spanning the United States, Canada, and Mexico, our dataset ensures wide-reaching access to verified small business contacts in the region.

Categories Tailored to Your Needs Includes highly relevant categories such as Small Business Contact Data, CEO Contact Data, B2B Contact Data, and Email Address Data to match your marketing and sales strategies.

Customizable and Flexible Choose from a wide range of filtering options to create datasets that meet your exact specifications, including filtering by industry, company size, geographic location, and more.

Best Price Guaranteed We pride ourselves on offering the most competitive rates without compromising on quality. When you partner with Success.ai, you receive superior data at the best value.

Seamless Integration Delivered in formats that integrate effortlessly with your CRM, marketing automation, or sales platforms, so you can start acting on the data immediately.

Use Cases: This dataset empowers you to:

Drive Sales Growth: Build and refine your sales pipeline by connecting directly with decision-makers in small businesses. Optimize Marketing Campaigns: Launch highly targeted email and phone outreach campaigns with verified contact data. Expand Your Network: Leverage the dataset to build relationships with small business owners and other key figures within the B2B landscape. Improve Data Accuracy: Enhance your existing databases with verified, enriched contact information, reducing bounce rates and increasing ROI. Industries Served: Whether you're in B2B SaaS, digital marketing, consulting, or any field requiring accurate and targeted contact data, this dataset serves industries of all kinds. It is especially useful for professionals focused on:

Lead Generation Business Development Market Research Sales Outreach Customer Acquisition What’s Included in the Dataset: Each profile provides:

Full Name Verified Email Address Phone Number (where available) Job Title Company Name Industry Company Size Location Skills and Professional Experience Education Background With over 170 million profiles, you can tap into a wealth of opportunities to expand your reach and grow your business.

Why High-Quality Contact Data Matters: Accurate, verified contact data is the foundation of any successful B2B strategy. Reaching small business owners and decision-makers directly ensures your message lands where it matters most, reducing costs and improving the effectiveness of your campaigns. By choosing Success.ai, you ensure that every contact in your pipeline is a genuine opportunity.

Partner with Success.ai for Better Data, Better Results: Success.ai is committed to delivering premium-quality B2B data solutions at scale. With our small business owner dataset, you can unlock the potential of North America's dynamic small business market.

Get Started Today Request a sample or customize your dataset to fit your unique...

Envestnet®| Yodlee®'s Consumer Transaction Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.

Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.

We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.

Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?

Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.

Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking

1. Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)

2. Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence

3. Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis

United States US: Total Business Enterprise R&D Personnel: Per Thousand Employment In Industry data was reported at 17.169 Per 1000 in 2020. This records an increase from the previous number of 15.152 Per 1000 for 2019. United States US: Total Business Enterprise R&D Personnel: Per Thousand Employment In Industry data is updated yearly, averaging 13.282 Per 1000 from Dec 2011 (Median) to 2020, with 10 observations. The data reached an all-time high of 17.169 Per 1000 in 2020 and a record low of 12.478 Per 1000 in 2012. United States US: Total Business Enterprise R&D Personnel: Per Thousand Employment In Industry data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.MSTI: Number of Researchers and Personnel on Research and Development: OECD Member: Annual.

Definition of MSTI variables 'Value Added of Industry' and 'Industrial Employment':

R&D data are typically expressed as a percentage of GDP to allow cross-country comparisons. When compiling such indicators for the business enterprise sector, one may wish to exclude, from GDP measures, economic activities for which the Business R&D (BERD) is null or negligible by definition. By doing so, the adjusted denominator (GDP, or Value Added, excluding non-relevant industries) better correspond to the numerator (BERD) with which it is compared to.

The MSTI variable 'Value added in industry' is used to this end:

It is calculated as the total Gross Value Added (GVA) excluding 'real estate activities' (ISIC rev.4 68) where the 'imputed rent of owner-occupied dwellings', specific to the framework of the System of National Accounts, represents a significant share of total GVA and has no R&D counterpart. Moreover, the R&D performed by the community, social and personal services is mainly driven by R&D performers other than businesses.

Consequently, the following service industries are also excluded: ISIC rev.4 84 to 88 and 97 to 98. GVA data are presented at basic prices except for the People's Republic of China, Japan and New Zealand (expressed at producers' prices).In the same way, some indicators on R&D personnel in the business sector are expressed as a percentage of industrial employment. The latter corresponds to total employment excluding ISIC rev.4 68, 84 to 88 and 97 to 98.

Graph and download economic data for Business Applications: Accommodation and Food Services in the United States (BABANAICS72SAUS) from Jul 2004 to May 2025 about business applications, accommodation, business, food, services, and USA.

According to an analysis conducted in 2023 of over *** companies targeting children and families in the United States, only ** percent of the businesses had a privacy-protective mindset and did not sell data. Under the California Privacy Rights Act amendment, companies are supposed to disclose if they sell users' personal data. Around ** percent of companies did not disclose whether they engaged in such practices.

This dataset provides an in-depth view of any specific company’s truck-based supply chain and its relationships with other facilities and companies within the continental US. We map US facilities (including factories, warehouses, and retail outlets) to companies. With this dataset, it is possible to track the movement of trucks and devices between locations to identify supply chain connections. Machine learning algorithms ingest 7-15bn daily events to estimate the volume of goods transported between locations. Consequently, we can map supply chain connections between: •Different companies (expressed as a percentage of volume transported). •Locations owned by the same company (e.g. warehouse to shop). With this novel geolocation approach, it is possible to "draw" a knowledge graph of any private or public company´s relations with other companies within the country. This solution, in the form of a dataset, provides an in-depth view into any specific company’s truck-based supply chain and its relationships with other facilities and companies within the continental United States. Use cases: - Identification and understanding of relations company-to-company: It helps to identify and infer relationships and connections between specific companies or facilities and between sectors/industries. - Identification and understanding of relations place-to-place: A logistics and domestic distribution supply chain can be mapped, both nationwide and state-wide in the US, and across countries in Europe. - Visualization and mapping of an entire supply chain network. - Tracking of products in any distribution or supply chain. - Risk assessment - Correlation analysis. - Disruption analysis. - Analysis of illicit networks and tracking of illegal use of corporate assets. - Improvement of casualty risk management. - Optimization of supply chain risk management. - Security and compliance. - Identification of not only the first tier of suppliers in the value chain, but also 2nd and 3rd tier suppliers, and more. Current largest use case: global corporation using it to model risk at a facility level (+100,000 locations).

Corporate Profits in the United States decreased to 3203.60 USD Billion in the first quarter of 2025 from 3312 USD Billion in the fourth quarter of 2024. This dataset provides the latest reported value for - United States Corporate Profits - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Graph and download economic data for Index of American Business Activity for United States (M12003USM516NNBR) from Jan 1855 to Dec 1970 about business, indexes, and USA.

Supermarket XYZ has been operating since 2008 and business flourished until 2016. They have a large database but they do not use them to achieve better business solutions. Their annual revenues have declined 10% and it seems to stay that way every year.

These datasets are used to analyse a supermarket in United States for the purpose of increasing revenue.

1. 50_Supermarket_Branches.csv contains the information of 50 supermarket branches such as their spending on the advertisement, administration and promotion, states and profits.

2. Ads_CTR_Optimisation.csv is based on the Click-Through Rates (CTR) from 10000 users in 10 different advertisements.

3. Market_Basket_Optimisation.csv . This dataset contains 7500 sales transactions in a week.

4. Supermarket_CustomerMembers.csv . This dataset can be used for customer segmentation.

These datasets in 'U.S. Supermarket Data' are available and legal for everyone who needs it for any kind of analytics project.