The U.S. manufacturing sector plays a central role in the economy, accounting for 20% of U.S. capital investment, 60% of the nation's exports and 70% of business R&D. Overall, the sector's market size, measured in terms of revenue is worth roughly $6 trillion, making it a major industry to do business with. So which U.S. states are the biggest for manufacturing? This article will explore the nation's top manufacturing states, measured by number of employees, based on MNI's database of 400,000 U.S. manufacturing companies.

Graph and download economic data for All Employees, Manufacturing (MANEMP) from Jan 1939 to Jul 2025 about headline figure, establishment survey, employment, manufacturing, and USA.

The Iowa Industrial New Jobs Training (260E) program provides employers expanding Iowa’s workforce with new employee training. The 260E program is designed to increase worker productivity and company profitability, and is administered by Iowa's 15 community colleges and financed through bonds sold by the colleges. Depending on wages paid, the participating businesses divert 1.5% or 3% of the Iowa state withholding taxes generated by the new positions to the community college to retire the bonds. Businesses may also be eligible to receive reimbursement for their on-the-job training expenses, and/or corporate tax credits. This dataset lists 260E contracts open in or after 2012, Qtr 2, and includes information on: the administering community college, participating employer, _location of employment, training expenses, and employment information. More on Iowa's 260E program.

Wages in Manufacturing in the United States remained unchanged at 28.96 USD/Hour in July. This dataset provides - United States Average Hourly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset includes the entire Industrial PinPointer database of manufacturing companies, which includes the 2009 D2 of 2 update. Eighteen (18) states have been updated in this delivery: Alaska, Arizona, Hawaii, Idaho, Massachusetts, Missouri, Nevada, New Hampshire, New York, Ohio, Oklahoma, Oregon, South Carolina, South Dakota, Tennessee, Utah, Wisconsin, and Wyoming. In addition to American Samoa, Guam, and the Commonwealth of the Northern Mariana Islands, two (2) US territories have been added to the dataset from the 2009 D1 of 2 update: Puerto Rico, and US Virgin Islands. This totals 48,930 companies. The database decreased by 65 companies from the 2009 D1 of 2 update. This dataset covers manufacturing locations in the 50 states, the District of Columbia, and US territories. Only those locations primarily engaged in manufacturing (SIC Codes 2000-3999) or those that are headquarters of manufacturing companies are included. SIC codes are not provided for 125 companies in the US territories. Where an employee count is available, only locations employing fifteen (15) or more people are included. Employee count is not available for the US territories; therefore, all locations primarily engaged in manufacturing are included for these territories. All text fields were set to upper case, leading and trailing spaces were trimmed from all text fields, and non-printable and diacritic characters were removed from all text fields per NGA's request.

This dataset provides information on the number of manufacturing establishments in each of the approximately 450 manufacturing industries, classified according to their employment size class and the state and county within which they are located. Each record is associated with a particular industry (4-digit SIC) and a particular county (or state or U.S. summary) and contains the number of establishments in seven employment size categories: 1-19 employees, 20-49, 50-99, 100-249, 250-499, 500-999 and 1000 employees or more. There is one record for each industry-county or industry-state combination with one or more manufacturing plants. The dataset is arranged by matrices, as follows: General Statistics: Matrix 201 U.S. by industry Matrix 202 Regions by industry Matrix 203 Divisions by industry Matrix 204 States by industry Matrix 205 SMSA's by industry Matrix 206 Selected counties by industry group Matrix 207 Selected cities by industry group Matrix 208 States, SMSA's, counties, and selected cities Detailed Statistics: Matrix 209 U.S. by industry Matrix 210 States and ADM components General Statistics by Employment Size of Establishment: Matrix 211 U.S. by industry Materials consumed: Matrix 212 U.S. by industry by 6-digit code for materials

What is the COVID-19 Economic Vulnerability Index?The COVID-19 Vulnerability Index (CVI) is a measurement of the negative impact that the coronavirus (COVID-19) crisis can have on employment based upon a region's mix of industries. For example, accommodation and food services are projected to lose more jobs as a result of the coronavirus (in the neighborhood of 50%) compared with utilities and healthcare (with none or little expected job contraction).This updated dataset contains 116 jobs attributes including the 10 most likely jobs to be impacted for each county, the total employment and employment by sector. An attribute list is included below.An average Vulnerability Index score is 100, representing the average job loss expected in the United States. Higher scores indicate the degree to which job losses may be greater — an index score of 200, for example, means the rate of job loss can be twice as large as the national average. Conversely, an index score of 50 would mean a possible job loss of half the national average. Regions heavily dependent on tourism with relatively high concentrations of leisure and hospitality jobs, for example, are likely to have high index scores. The Vulnerability Index only measures the impact potential related to the mix of industry employment. The index does not take into account variation due to a region’s rate of virus infection, nor does it factor in local government's policies in reaction to the virus. For more detail, please see this description.MethodologyThe index is based on a model of potential job losses due to the COVID-19 outbreak in the United States. Expected employment losses at the subsector level are based upon inputs which include primary research on expert testimony; news reports for key industries such as hotels, restaurants, retail, and transportation; preliminary release of unemployment claims; and the latest job postings data from Chmura's RTI database. The forecast model, based on conditions as of March 23, 2020, assumes employment in industries in each county/region would change at a similar rate as employment in national industries. The projection estimates that the United States could lose 15.0 million jobs due to COVID-19, with over half of the jobs lost in hotels, food services, and entertainment industries. Contact Chmura for further details.Attribute ListFIPSCounty NameStateTotal JobsWhite Collar JobsBlue Collar JobsService JobsWhite Collar %Blue Collar %Service %Government JobsGovernment %Primarily Self-Employed JobsPrimarily Self-Employed %Job Change, Last Ten YearsIndustry 1 NameIndustry 1 EmplIndustry 1 %Industry 2 NameIndustry 2 EmplIndustry 2 %Industry 3 NameIndustry 3 EmplIndustry 3 %Industry 4 NameIndustry 4 EmplIndustry 4 %Industry 5 NameIndustry 5 EmplIndustry 5 %Industry 6 NameIndustry 6 EmplIndustry 6 %Industry 7 NameIndustry 7 EmplIndustry 7 %Industry 8 NameIndustry 8 EmplIndustry 8 %Industry 9 NameIndustry 9 EmplIndustry 9 %Industry 10 NameIndustry 10 EmplIndustry 10 %All Other IndustriesAll Other Industries EmplAll Other Industies %Agriculture, Food & Natural Resources EmplArchitecture and Construction EmplArts, A/V Technology & Communications EmplBusiness, Management & Administration EmplEducation & Training EmplFinance EmplGovernment & Public Administration EmplHealth Science EmplHospitality & Tourism EmplHuman Services EmplInformation Technology EmplLaw, Public Safety, Corrections & Security EmplManufacturing EmplMarketing, Sales & Service EmplScience, Technology, Engineering & Mathematics EmplTransportation, Distribution & Logistics EmplAgriculture, Food & Natural Resources %Architecture and Construction %Arts, A/V Technology & Communications %Business, Management & Administration %Education & Training %Finance %Government & Public Administration %Health Science %Hospitality & Tourism %Human Services %Information Technology %Law, Public Safety, Corrections & Security %Manufacturing %Marketing, Sales & Service %Science, Technology, Engineering & Mathematics %Transportation, Distribution & Logistics %COVID-19 Vulnerability IndexAverage Wages per WorkerAvg Wages Growth, Last Ten YearsUnemployment RateUnderemployment RatePrime-Age Labor Force Participation RateSkilled Career 1Skilled Career 1 EmplSkilled Career 1 Avg Ann WagesSkilled Career 2Skilled Career 2 EmplSkilled Career 2 Avg Ann WagesSkilled Career 3Skilled Career 3 EmplSkilled Career 3 Avg Ann WagesSkilled Career 4Skilled Career 4 EmplSkilled Career 4 Avg Ann WagesSkilled Career 5Skilled Career 5 EmplSkilled Career 5 Avg Ann WagesSkilled Career 6Skilled Career 6 EmplSkilled Career 6 Avg Ann WagesSkilled Career 7Skilled Career 7 EmplSkilled Career 7 Avg Ann WagesSkilled Career 8Skilled Career 8 EmplSkilled Career 8 Avg Ann WagesSkilled Career 9Skilled Career 9 EmplSkilled Career 9 Avg Ann WagesSkilled Career 10Skilled Career 10 EmplSkilled Career 10 Avg Ann Wages

The National Science Foundation, the Department of Labor and the Department of Energy have programs that support training for jobs in energy and manufacturing related workforce training programs. This dataset provides a searchable list of the training programs in these areas showing the subjects being taught, grantee, project title, and state. In some cases the list also shows the certificates provided by the courses. The list is still a work in progress and will be updated as more information is obtained. It may contain incomplete information, unintentional omissions and errors in topic identification and taxonomy. Please contact us with suggestions or corrections.

Overview

This dataset contains a list of the top 100 companies, ranked by revenue according to Fortune 500. It contains information about the company's revenue in USD, revenue growth percentage, number of employees (as of 2023 or fiscal year 2022), the type of industry the company is and it's headquarters.

Dataset Structure

1. Rank - Rank of the Company by Revenue
2. Name - Name of the Company
3. Industry - The type of Industry the Company is
4. Revenue (USD millions) - Revenue generated by the Company in US Dollars in Millions
5. Revenue Growth - Percentage Revenue Growth of the Company
6. Employees - Total Number of Employees in the Company
7. Headquarters - City, State where the Headquarters of the Company is located

Usage

This dataset is suitable for performing Exploratory Data Analysis. Potential analysis could include highest revenue generating industries, top companies by revenue, companies/industries displaying maximum revenue growth, revenue per employee analysis.

Visualization tools such as Matplotlib and Seaborn could be utilized for a more in-depth analysis to create visual representations of the findings.

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.

API Features:

• Real-Time Updates: Our APIs deliver real-time updates, ensuring that the contact data your business relies on is always current and accurate.
• High Volume Handling: Designed to support up to 860k API calls per day, our system is built for scalability and responsiveness, catering to enterprises of all sizes.
• Flexible Integration: Easily integrate with CRM systems, marketing automation tools, and other enterprise applications to streamline your workflows and enhance productivity.

Benefits of the EU Premium Dataset:

Targeted Reach: Reach potential leads with detailed insights including email addresses, phone numbers, job titles, and more, specifically within the EU markets. Enhanced Lead Quality: Every profile is thoroughly verified, enhancing the quality of your outreach and increasing the likelihood of successful engagements. Best Price Guarantee: We are committed to providing these extensive services at the most competitive prices, ensuring that you receive the best value for your investment.

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: So...

Context:

The Occupational Employment Statistics (OES) and National Compensation Survey (NCS) programs have produced estimates by borrowing from the strength and breadth of each survey to provide more details on occupational wages than either program provides individually. Modeled wage estimates provide annual estimates of average hourly wages for occupations by selected job characteristics and within geographical location. The job characteristics include bargaining status (union and nonunion), part- and full-time work status, incentive- and time-based pay, and work levels by occupation.

Direct estimates are based on survey responses only from the particular geographic area to which the estimate refers. In contrast, modeled wage estimates use survey responses from larger areas to fill in information for smaller areas where the sample size is not sufficient to produce direct estimates. Modeled wage estimates require the assumption that the patterns to responses in the larger area hold in the smaller area.

The sample size for the NCS is not large enough to produce direct estimates by area, occupation, and job characteristic for all of the areas for which the OES publishes estimates by area and occupation. The NCS sample consists of 6 private industry panels with approximately 3,300 establishments sampled per panel, and 1,600 sampled state and local government units. The OES full six-panel sample consists of nearly 1.2 million establishments.

The sample establishments are classified in industry categories based on the North American Industry Classification System (NAICS). Within an establishment, specific job categories are selected to represent broader occupational definitions. Jobs are classified according to the Standard Occupational Classification (SOC) system.

Content:

Summary: Average hourly wage estimates for civilian workers in occupations by job characteristic and work levels. These data are available at the national, state, metropolitan, and nonmetropolitan area levels.

Frequency of Observations: Data are available on an annual basis, typically in May.

Data Characteristics: All hourly wages are published to the nearest cent.

Acknowledgements:

This dataset was taken directly from the Bureau of Labor Statistics and converted to CSV format.

Inspiration:

This dataset contains the estimated wages of civilian workers in the United States. Wage changes in certain industries may be indicators for growth or decline. Which industries have had the greatest increases in wages? Combine this dataset with the Bureau of Labor Statistics Consumer Price Index dataset and find out what kinds of jobs you would need to afford your snacks and instant coffee!

HitHorizons Manufacturing Company Data API gives access to aggregated firmographic data on 4,289,762 manufacturing companies from the whole of Europe and beyond.

Company registration data: company name national identifier and its type registered address: street, postal code, city, state / province, country business activity: SIC code, local activity code with classification system year of establishment company type location type

Sales and number of employees data: sales in EUR, USD and local currency (with local currency code) total number of employees sales and number of employees accuracy local number of employees (in case of multiple branches) companies’ sales and number of employees market position compared to other companies in a country / industry / region

Industry data: size of the whole industry size of all companies operating within a particular SIC code benchmarking within a particular country or industry regional benchmarking (EU 27, state / province)

Contact details: company website company email domain (without person’s name)

Invoicing details available for selected countries: company name company address company VAT number

Non Farm Payrolls in the United States increased by 73 thousand in July of 2025. This dataset provides the latest reported value for - United States Non Farm Payrolls - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Number of employees by North American Industry Classification System (NAICS) and type of employee, last 5 years.

Displays a representation of where all the surveyed businesses across York Region are located. This data is collected through the Region’s annual comprehensive employment survey and each record contains employment and business contact information about each business with the exception of home and farm-based businesses. Home-based businesses are not included as they are distributed throughout residential communities within the Region and are difficult to survey. Employment data for farm-based businesses are collected through the Census of Agriculture conducted by Statistics Canada, and are not included in the York Region Employment Survey dataset.Update Frequency: Not PlannedDate Created: 17/03/2023Date Modified: 17/03/2023Metadata Date: 17/03/2023Citation Contacts: York Region, Long Range PlanningAttribute DefinitionsBUSINESSID: Unique key to identify a business.NAME: The common business name used in everyday transactions. FULL_ADDRESS: Full street address of the physical address. (This field concatenates the following fields: Street Number, Street Name, Street Type, Street Direction)STREET_NUM: Street number of the physical addressSTREET_NAME: Street name of the physical addressSTREET_TYPE: Street type of the physical addressSTREET_DIR: Street direction of the physical addressUNIT_NUM: Unit number of the physical addressCOMMUNITY: Community name where the business is physically locatedMUNICIPALITY: Municipality where the business is physically locatedPOST_CODE: Postal code corresponding to the physical street addressEMPLOYEE_RANGE: The numerical range of employees working in a given firm. PRIM_NAICS, PRIM_NAICS_DESC: The Primary 5-digit NAIC code defines the main business activity that occurs at that particular physical business location.SEC_NAICS, SEC_NAICS_DESC: If there is more than one business activity occurring at a particular business location (that is substantially different from the primary business activity), then a secondary NAIC is assigned.PRIM_BUS_CLUSTER, SEC_BUS_CLUSTER: A business cluster is defined as a geographic concentration of interconnected businesses and institutions in a common industry that both compete and cooperate. As defined by York Region, this field indicates the primary business cluster that this business belongs to.BUS_ACTIVITY_DESC: This is a comment box with a detailed text description of the business activity.TRAFFIC_ZONE: Specifies the traffic zone in which the business is located. MANUFACTURER: Indicates whether or not the business manufactures at the physical business location. CAN_HEADOFFICE: The business at this location is considered the Canadian head office.HEADOFFICEPROVSTATE: Indicates which state or province the head office is located if the head office is located in Canada (outside of Ontario) or in the United StatesHEADOFFICECOUNTRY: Indicates which country the head office is locatedYR_CURRENTLOC: Indicates the year that the business moved into its current address.MAIL_FULL_ADDRESS: The mailing address is the address through which a business receives postal service. This may or may not be the same as the physical street address.MAIL_STREET_NUM, MAIL_STREET_NAME, MAIL_STREET_TYPE, MAIL_STREET_DIR, MAIL_UNIT_NUM, MAIL_COMMUNITY, MAIL_MUNICIPALITY, MAIL_PROVINCE, MAIL_COUNTRY, MAIL_POST_CODE, MAIL_POBOX: Mailing address fields are similar to street address fields and in most cases will be the same as the Street Address. Some examples where the two addresses might not be the same include, multiple location businesses, home-based businesses, or when a business receives mail through a P.O. Box.WEBSITE: The General/Main business website.GEN_BUS_EMAIL: The general/main business e-mail address for that location.PHONE_NO: The general/main phone number for the business location.PHONE_EXT: The extension (if any) for the general/main business phone number.LAST_SURVEYED: The date the record was last surveyedLAST_UPDATED: The date the record was last updatedUPDATEMETHOD: Displays how the business was last updated, based on a predetermined list.X_COORD, Y_COORD: The x,y coordinates of the surveyed business locationFrequently Asked Questions How many businesses are included in the 2022 York Region Business Directory? The 2022 York Region Business Directory contains just over 34,000 business listings. In the past, businesses were annually surveyed, either in person or by telephone to improve the accuracy of the directory. Due to the COVID-19 Pandemic, a survey was not complete in 2020 and 2021. The Region may return to annual surveying in future years, however the next employment survey will be in 2024. This listing also includes home-based businesses that participated in the 2022 employment survey. What is a NAIC code? The North American Industrial Classification (NAIC) coding system is a hierarchical classification system developed in Canada, Mexico and the United States. It was developed to allow for the comparison of business and employment information across a variety of industry categories. The NAICS has a hierarchical structure, designed as follows: Two-digits = sector (e.g., 31-33 contain the Manufacturing sectors) Three-digits = subsector (e.g., 336 = Transportation Equipment Manufacturing) Four-digits = industry group (e.g., 3361 = Motor Vehicle Manufacturing) Five-digits = industry (e.g., 33611 = Automobile and Light Duty Motor Vehicle Manufacturing) For more information on the NAIC coding system click here How do I add or update my business information in the York Region Business Directory? To add or update your business information, please select one of the following methods: • Email: Please email businessdirectory@york.ca to request to be added to the Business Directory. • Online: Go to www.york.ca/employmentsurvey and participate in the employment survey - note, this will only be active in 2024 when the Region performs its next employment survey There is no charge for obtaining a basic listing of your business in the York Region Business Directory. How up-to-date is the information? This directory is based on the 2022 York Region Employment Survey, a survey of businesses which attempts to gather information from all businesses across York Region. In instances where we were unable to gather information, the most recent data was used. Farm-based businesses have not been included in the survey and home-based businesses that participated in the 2022 survey are included in the dataset. The date that the business listing was last updated is located in the LastUpdate column in the attached spreadsheet. Are different versions of the York Region Business Directory available? Yes, the directory is available in two online formats: • An interactive, map-based directory searchable by company name, street address, municipality and industry sector. • The entire dataset in downloadable Microsoft Excel format via York Region's Open Data Portal. This version of the York Region Business Directory 2022 is offered free of charge. The Directory allows for the detailed analysis of business and employment trends, as well as the construction of targeted contact lists. To view the map-based directory and dataset, go to: 2022 Business Directory - Map Is there any analysis of business and employment trends in York Region? Yes. The "2022 Employment and Industry Report" contains information on employment trends in York Region and is based on results from the employment survey. please visit www.york.ca/york-region/plans-reports-and-strategies/employment-and-industry-report to view the report. What other resources are available for York Region businesses? York Region offers an export advisory service and a number of other business development programs and seminars for interested individuals. For details, consult the York Region Economic Strategy Branch. Who do I contact to obtain more information about the Directory? For more information on the York Region Business Directory, contact the Planning and Economic Development Branch at: businessdirectory@york.ca.

Techsalerator’s Business Technographic Data for United States provides a thorough and insightful collection of information essential for businesses, market analysts, and technology vendors. This dataset offers a deep dive into the technological landscape of companies operating in United States, capturing and categorizing data related to their technology stacks, digital tools, and IT infrastructure.

Please reach out to us at info@techsalerator.com or https://www.techsalerator.com/contact-us

Top 5 Most Utilized Data Fields Company Name: This field lists the name of the company being analyzed. Understanding the companies helps technology vendors target their solutions and enables market analysts to evaluate technology adoption trends within specific businesses. Technology Stack: This field details the technologies and software solutions a company utilizes, such as CRM systems, ERP software, and cloud services. Knowledge of a company’s technology stack is vital for understanding its operational capabilities and technology needs. Deployment Status: This field indicates whether the technology is currently in use, planned for deployment, or under evaluation. This status helps vendors gauge the level of interest and current adoption among businesses. Industry Sector: This field identifies the industry sector in which the company operates, such as finance, manufacturing, or retail. Segmenting by industry sector helps vendors tailor their offerings to specific market needs and trends. Geographic Location: This field provides the geographic location of the company's headquarters or primary operations within United States. This information is useful for regional market analysis and understanding local technology adoption patterns. Top 5 Technology Trends in the United States Artificial Intelligence and Machine Learning: AI and ML continue to drive innovation across various sectors, from autonomous vehicles and healthcare to finance and customer service. Key advancements include natural language processing, computer vision, and reinforcement learning. Cloud Computing and Edge Computing: The shift towards cloud computing remains strong, with major providers like AWS, Azure, and Google Cloud leading the way. Edge computing is also gaining traction, enabling faster processing and data analysis closer to the source, which is crucial for IoT applications. 5G Technology: The rollout of 5G networks is transforming connectivity, enabling faster data speeds, lower latency, and new applications in IoT, smart cities, and augmented reality (AR). Major telecom companies and technology providers are heavily invested in this technology. Cybersecurity and Privacy: As digital threats become more sophisticated, there is an increased focus on cybersecurity solutions, including threat detection, data encryption, and privacy protection. Innovations in this space aim to combat ransomware, data breaches, and other cyber risks. Blockchain and Decentralized Finance (DeFi): Blockchain technology is expanding beyond cryptocurrencies, with applications in supply chain management, digital identity, and smart contracts. DeFi is a growing sector within blockchain, offering decentralized financial services and products. Top 5 Companies with Notable Technographic Data in the United States Microsoft: A leading technology company known for its software, cloud computing services (Azure), and AI research. Microsoft's diverse portfolio includes operating systems, enterprise solutions, and gaming (Xbox). Google (Alphabet Inc.): A major player in search engines, cloud computing, AI, and consumer electronics. Google is at the forefront of innovations in machine learning, autonomous driving (Waymo), and digital advertising. Amazon: Known for its e-commerce platform, Amazon is also a significant force in cloud computing (AWS), AI, and logistics. AWS is a leading cloud service provider, and Amazon's technology initiatives span various industries. Apple Inc.: Renowned for its consumer electronics, including iPhones, iPads, and Macs. Apple is also investing in emerging technologies such as AR, wearable technology (Apple Watch), and health tech. IBM: A historic leader in technology and consulting services, IBM focuses on enterprise solutions, cloud computing, AI (IBM Watson), and quantum computing. The company is known for its research and development in cutting-edge technologies. Accessing Techsalerator’s Business Technographic Data If you’re interested in obtaining Techsalerator’s Business Technographic Data for United States, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide a customized quote based on the number of data fields and records you need, with the dataset available for delivery within 24 hours. Ongoing access options can also be discussed as needed.

Included Data Fields Company Name Technology Stack Depl...

Key Table Information.Table Title.Island Areas: Selected Statistics by Manufacturing Industry, Legal Form of Organization, and Employment Size of Establishments for Puerto Rico: 2022.Table ID.ISLANDAREASIND2022.IA2200IND18.Survey/Program.Economic Census of Island Areas.Year.2022.Dataset.ECNIA Economic Census of Island Areas.Source.U.S. Census Bureau, 2022 Economic Census of Island Areas, Core Statistics.Release Date.2024-12-19.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.2022 Economic Census of Island Areas tables are released on a flow basis from June through December 2024.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe. The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in Puerto Rico, have paid employees, and are classified in one of eighteen in-scope sectors defined by the 2022 NAICS..Sponsor.U.S. Department of Commerce.Methodology.Data Items and Other Identifying Records.Number of establishmentsNumber of employeesAnnual payroll ($1,000)Value added ($1,000)Total cost of supplies and/or materials ($1,000)Sales, value of shipments, or revenue ($1,000)Range indicating imputed percentage of total annual payrollRange indicating imputed percentage of total employeesRange indicating imputed percentage of total sales, value of shipments, or revenueEach record includes a LFO code, which represents a specific legal form of organization category.Each record includes an EMPSZES code, which represents a specific employment size category of establishments.The data are shown for legal form of organization and employment size of establishments.Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the Economic Census of Island Areas are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed..Geography Coverage.The data are shown for employer establishments and firms that vary by industry:At the Territory level for Puerto RicoFor information about economic census geographies, including changes for 2022, see Economic Census: Economic Geographies..Industry Coverage.The data are shown for Puerto Rico at the 2- through 3-digit 2022 NAICS code levels for the manufacturing industry.For information about NAICS, see Economic Census Code Lists..Sampling.The Economic Census of Island Areas is a complete enumeration of establishments located in the islands (i.e., all establishments on the sampling frame are included in the sample). Therefore, the accuracy of tabulations is not affected by sampling error..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0044).The primary method of disclosure avoidance protection is noise infusion. Under this method, the quantitative data values such as sales or payroll for each establishment are perturbed prior to tabulation by applying a random noise multiplier (i.e., factor). Each establishment is assigned a single noise factor, which is applied to all its quantitative data value. Using this method, most published cell totals are perturbed by at most a few percentage points.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. For more information on disclosure avoidance, see Methodology for the 2022 Economic Census- Island Areas..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, see Methodology for the 2022 Economic Census- Island Areas.For more information about survey questionnaires, Primary Business Activity/NAICS codes, and NAPCS codes, see Economic Census Technical Documentation..Weights.Because the Economic Census of Island Areas is a complete enumeration, there is no sample weighting..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector00.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link t...

Transport for NSW provides projections of employment at the small area (Travel Zone or TZ) level for NSW. The latest version is Travel Zone Projections 2024 (TZP24), released in January 2025. TZP24 replaces the previously published TZP22. The projections are developed to support a strategic view of NSW and are aligned with the NSW Government Common Planning Assumptions. TZP24 Employment Projections are for employed persons by place of work. They are provided by Industry using two breakdowns:

33 industry categories (equivalent to the ABS 1-digit Australia and New Zealand Standard Industrial Classification (ANZSIC) codes with the exception of Manufacturing which is at 2-digit level).

4 Broad Industry Categories (groupings of the above).

The projections in this release, TZP24, are presented annually from 2021 to 2031 and 5-yearly from 2031 to 2066, and are in TZ21 geography. Please note, TZP24 is based on best available data as at early 2024, and the projections incorporate results of the National Census conducted by the ABS in August 2021. Key Data Inputs used:

TZP24 Workforce Projections

Census 2021 Place of Work by Destination Zone - ABS

NSW Intergenerational Report - NSW Treasury

SA4 Employment by industry projections - Victoria University

Future Employment Development Database (FEDD) - a custom dataset compiled by TfNSW between August 2023 and February 2024, that presents the number of jobs expected from major projects based on publicly available documents.

For a summary of the TZP24 Projections method please refer to the TZP24 Factsheet. For more detail on the projection process please refer to the TZP24 Technical Guide. Additional land use information for population and workforce as well as Travel Zone 2021 boundaries for NSW (TZ21) and concordance files are also available for download on the Open Data Hub. Visualisations of the employment projections are available on the Transport for NSW Website. Cautions The TZP24 dataset represents one view of the future aligned with the NSW Government Common Planning Assumptions for population and employment projections. The projections are not based on specific assumptions about future new transport infrastructure, but do take into account known land-use developments underway or planned, and strategic plans.

TZP24 is a strategic state-wide dataset and caution should be exercised when considering results at detailed breakdowns.

The TZP24 outputs represent a point in time set of projections (as at early -2024).

The projections are not government targets.

Travel Zone (TZ) level outputs are projections only and should be used as a guide. As with all small area data, aggregating of travel zone projections to higher geographies leads to more robust results.

As a general rule, TZ-level projections are illustrative of a possible future only.

More specific advice about data reliability for the specific variables projected is provided in the “Read Me” page of the Excel format summary spreadsheets on the TfNSW Open Data Hub.

Caution is advised when comparing TZP24 with the previous set of projections (TZP22) due to addition of new data sources for the most recent years, and adjustments to methodology.

Further cautions and notes can be found in the TZP24 Technical Guide.

This dataset provides values for WAGES IN MANUFACTURING reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.