The net job and business growth indicator measures the annual change in both the number of firms and the number of employees between 1978 and 2022. The data is categorized by the size of the firm: those with 1-19 employees, those with between 20 and 499 employees, and those with more than 500 employees.

This data contributes to the big picture of economic conditions in Champaign County. More firms and larger employment numbers are generally positive economic indicators, but any strictly economic indicator should be considered in the context of other factors.

The number of firms and number of employees show very different trends.

Historically, there have been significantly more firms with 1-19 employees than firms in the larger two size categories. The number of firms with 1-19 employees has also been relatively consistent until 2021: there were 95 fewer such firms in 2021 than 1978, and the largest year-to-year change in that 43-year period of analysis was a -3.2% decrease between 1979 and 1980. However, there were 437 fewer such firms in 2022 than 1978. There was a decrease in these firms of 12.5% from 2021 to 2022, the only double-digit year-to-year change and the largest year-to-year change over 44 years.

The larger two size categories have shown an increasing trend over the period of analysis. There were 43 more firms with 20-499 employees in 2022 than 1978, a total increase of 9%. The number of firms with more than 500 employees almost doubled, increasing by 206 firms from 212 in 1978 to 418 in 2022, a total increase of 97.2%.

The trends of employment also vary based on firm size. Firms with 1-19 employees have consistently, and unsurprisingly, accounted for less of the total employment than the larger two categories. Employment in firms with 1-19 employees has also remained relatively consistent over the period of analysis. Employment in firms with more than 500 employees saw an overall trend of growth, interrupted by brief and intermittent decreases, between 1978 and 2022. Employment in the middle category (firms with between 20 and 499 employees) was also greater in 2022 than in 1978.

This data is from the U.S. Census Bureau’s Business Dynamics Statistics Data Tables. This data is at the geographic scale of the Champaign-Urbana Metropolitan Statistical Area (MSA), which is comprised of Champaign and Piatt Counties, or a larger area than the cities or Champaign County.

Source: U.S. Census Bureau; 2022 Business Dynamics Statistics Data Tables; "BDSFSIZE - Business Dynamics Statistics: Firm Size: 1978-2022"; retrieved 21 October 2024.

Data from Fortune 500's 2023 ranking.
Includes data on top 1000 companies w/ additional info (Stock symbol/*ticker*, CEO name).

Update (New dataset): 2024 Fortune 1000 Companies

What Is the Fortune 1000?

From Investopedia:

The Fortune 1000 is an annual list of the 1000 largest American companies maintained by the popular magazine Fortune Fortune ranks the eligible companies by revenue generated from core operations, discounted operations, and consolidated subsidiaries Since revenue is the basis for inclusion, every company is authorized to operate in the United States and files a 10-K or comparable financial statement with a government agency -- .

Project Background

Fortune magazine publishes this list every year and some lists can be found from different sources. From looking at this year's available datasets, some features were missing or could not be found. This was built from scraping the standard features as well as what's included on Company Info (such as CEO, Ticker and website) from the Fortune magazine website. Details on how the data was generated can be found on this notebook where a few of the features were also visualized.

The source code from the 2023 fortune 500 Ranking includes 1000 companies. A reference page (slug) to additional info is included for each companies which were also scrapped to complete the dataset.

The Dataset

Available formats: csv, parquet

Features are follows:

[Note: References to datatypes are relevant when using the parquet file; Labels refer to the original website names]

• Rank
    dtype: int64; Label: Rank
• Company
    dtype: object; Label: Company
• Ticker
    dtype: object; Label: Ticker
• Sector
    dtype: category; Label: Sector
• Industry
    dtype: category; Label: Industry
• Profitable
    dtype: category; Label: Profitable
• Founder_is_CEO
    dtype: category; Label: Founder is CEO
• FemaleCEO
    dtype: category; Label: Female CEO
• Growth_in_Jobs
    dtype: category; Label: Growth in Jobs
• Change_in_Rank
    dtype: float64; Label: Change in Rank (Full 1000)
• Gained_in_Rank
    dtype: category; Label: Gained in Rank
• Dropped_in_Rank
    dtype: category; Label: Dropped in Rank
• Newcomer_to_the_Fortune500
    dtype: category; Label: Newcomer to the Fortune 500
• Global500
    dtype: category; Label: Global 500
• Best_Companies
    dtype: category; Label: Best Companies
• Number_of_employees
    dtype: int64; Label: Employees
• MarketCap_March31_M
    dtype: float64; Label: Market Value — as of March 31, 2023 ($M)
• Revenues_M
    dtype: int64; Label: Revenues ($M)
• RevenuePercentChange
    dtype: float64; Label: Revenue Percent Change
• Profits_M
    dtype: int64; Label: Profits ($M)
• ProfitsPercentChange
    dtype: float64; Label: Profits Percent Change
• Assets_M
    dtype: int64; Label: Assets ($M)
• CEO
    dtype: object; Label: CEO
• Country
    dtype: category; Label: Country
• HeadquartersCity
    dtype: object; Label: Headquarters City
• HeadquartersState
    dtype: category; Label: Headquarters State
• Website
    dtype: object; Label: Website
• CompanyType
    dtype: category; Label: Company type
• Footnote
    dtype: object; Label: Footnote
• MarketCap_Updated_M
    dtype: float64; Label: Market value ($M)
• Updated
    dtype: datetime64[ns]; Label: Updated Click to add a cell.

Key Table Information.Table Title.Annual Business Survey: Employment Size of Firm Statistics for Employer Firms by Sector, Sex, Ethnicity, Race, and Veteran Status for the U.S., States, Metro Areas, and Counties: 2022.Table ID.ABSCS2022.AB2200CSA04.Survey/Program.Economic Surveys.Year.2022.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2024-12-19.Release Schedule.The Annual Business Survey (ABS) occurs every year, beginning in reference year 2017.For more information about ABS planned data product releases, see Tentative ABS Schedule..Dataset Universe.The dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Methodology.Data Items and Other Identifying Records.Number of employer firms (firms with paid employees)Sales and receipts of employer firms (reported in $1,000s of dollars)Number of employees (during the March 12 pay period)Annual payroll (reported in $1,000s of dollars)These data are aggregated by sex, ethnicity, race, and veteran status when classifiable.The data are also shown for the employment size of firms (during the March 12 pay period):Employment Size: Firms with no employees Firms with 1 to 4 employees Firms with 5 to 9 employees Firms with 10 to 19 employees Firms with 20 to 49 employees Firms with 50 to 99 employees Firms with 100 to 249 employees Firms with 250 to 499 employees Firms with less than 500 employees Firms with 500 employees or more 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 ABS are employer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The 2022 reference year data are shown for the total for all sectors (00) and the 2-digit NAICS code levels for:United StatesStates and the District of ColumbiaIn addition, data are shown for the total for all sectors (00) for:Metropolitan Statistical AreasCountiesFor information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00"), and at the 2-digit NAICS code level depending on geography. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Office of Notaries (NAICS 541120)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.The ABS sample includes firms that are selected with certainty if they have known research and development activities, were included in the 2022 BERD sample, or have high receipts, payroll, or employment. Total sample size is 850,000 firms. The universe is stratified by state, industry group, and expected demographic group. Firms selected to the sample receive a questionnaire. For all data on this table, firms not selected into the sample are represented with administrative, 2022 Economic Census, or other economic surveys records.For more information about the sample design, see Annual Business Survey Methodology..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. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0351).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business' data or identity.To comply with data quality standards, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the Annual Business Survey Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data a...

Dataset contains US Retail companies with company size from 200-500 workers. For each company, all workers were scrapped as well.

For mode details about scrapping code, you can check my article or GitHub code

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.

Employment for all employees by enterprise size and North American Industry Classification System (NAICS), last 5 years.

We have successfully extracted a comprehensive news dataset from CNBC, covering not only financial updates but also an extensive range of news categories relevant to diverse audiences in Europe, the US, and the UK. This dataset includes over 500,000 records, meticulously structured in JSON format for seamless integration and analysis.

Diverse News Segments for In-Depth Analysis

This extensive extraction spans multiple segments, such as:

• Business and Market Analysis: Stay updated on major companies, mergers, and acquisitions.
• Technology and Innovation: Explore developments in AI, cybersecurity, and digital transformation.
• Economic Forecasts: Access insights into GDP, employment rates, inflation, and other economic indicators.
• Geopolitical Developments: Understand the impact of political events and global trade dynamics on markets.
• Personal Finance: Learn about saving strategies, investment tips, and real estate trends.

Each record in the dataset is enriched with metadata tags, enabling precise filtering by region, sector, topic, and publication date.

Why Choose This Dataset?

The comprehensive news dataset provides real-time insights into global developments, corporate strategies, leadership changes, and sector-specific trends. Designed for media analysts, research firms, and businesses, it empowers users to perform:

• Trend Analysis
• Sentiment Analysis
• Predictive Modeling

Additionally, the JSON format ensures easy integration with analytics platforms for advanced processing.

Access More News Datasets

Looking for a rich repository of structured news data? Visit our news dataset collection to explore additional offerings tailored to your analysis needs.

Sample Dataset Available

To get a preview, check out the CSV sample of the CNBC economy articles dataset.

Walmart Inc. is an American multinational retail corporation that operates a chain of hypermarkets (also called supercenters), discount department stores, and grocery stores in the United States, headquartered in Bentonville, Arkansas. The company was founded by Sam Walton in nearby Rogers, Arkansas in 1962 and incorporated under Delaware General Corporation Law on October 31, 1969. It also owns and operates Sam's Club retail warehouses. In India, Walmart operates under the name of Flipkart Wholesale.

As of July 31, 2022, Walmart has 10,585 stores and clubs in 24 countries, operating under 46 different names. Out of which we have chosen 45 stores for basic analysis.

Walmart is the world's largest company by revenue, with about US$570 billion in annual revenue, according to the Fortune Global 500 list in May 2022.

How Walmart uses Big Data?

• Improving Store Checkout: By using Predictive Analysis, the stores can anticipate demand at a certain week and determine how many Sales Representatives / Employees are needed.
• Managing the Steps of Supply Chain: The company optimizes the routes to the shipping dock and tracks the number of times the product is accessed before it reaches the Customer's destination. Also, it uses the data to analyze transportation lanes and routes for the company's trucks. These data help Walmart keep transportation costs down and schedule an appropriate time for drivers.
• Optimizing Product Assortment: By analyzing customer preferences and shopping patterns, Walmart accelerates the decision-making on how to maintain stocks. Big Data provides insights on new items and discontinued products.
• Personalizing Shopping Experience: With Big Data, Walmart analyzes the shopping preferences of the customers to develop a consistent and delightful shopping experience. and much more...

Welcome to the North America Data: Your Gateway to Strategic Connections Across the Americas

In today’s fast-evolving business landscape, having the right data at your fingertips is crucial for success. North America Data offers an unmatched resource designed to empower businesses by providing access to key decision-makers across the vast and diverse markets of North and South America. Our meticulously curated database serves as the cornerstone of your strategic outreach efforts, enabling you to connect with the right people in the right places at the right time.

What Makes Our Data Unique?

Depth and Precision
Our database is more than just a collection of names and contact details—it’s a gateway to deep, actionable insights about the people who shape industries. We go beyond basic data points to offer a nuanced understanding of top executives, owners, founders, and influencers. Whether you're looking to connect with a CEO of a Fortune 500 company or a founder of a dynamic startup, our data provides the precision you need to identify and engage the most relevant decision-makers.

Our Data Sourcing Excellence

Reliability and Integrity
Our data is sourced from a variety of authoritative channels, ensuring that every entry is both reliable and relevant. We draw from respected business directories, publicly available records, and proprietary research methodologies. Each piece of data undergoes a rigorous vetting process, meticulously checked for accuracy, to ensure that you can trust the integrity of the information you receive.

Primary Use-Cases and Industry Verticals

Versatility Across Sectors
The North America Data is a versatile tool designed to meet the needs of a wide range of industries. Whether you're in finance, manufacturing, technology, healthcare, retail, hospitality, energy, transportation, or any other sector, our database provides the critical insights necessary to drive your business forward. Use our data to:

• Expand Market Presence: Identify and connect with key players in new markets.
• Forge Strategic Partnerships: Reach out to potential collaborators and investors.

• Conduct Market Research: Gain a deeper understanding of industry trends and dynamics.

  Seamless Integration with Broader Data Solutions

Comprehensive Business Intelligence
Our North America Data is not an isolated resource; it’s a vital component of our comprehensive business intelligence suite. When combined with our global datasets, it provides a holistic view of the global business landscape. This integrated approach enables businesses to make well-informed decisions, tapping into insights that span across continents and sectors.

Geographical Coverage Across the Americas

Pan-American Reach
Our database covers the entirety of North and South America, offering a robust range of contacts across numerous countries, including but not limited to:

• United States
• Canada
• Mexico
• Brazil
• Argentina
• Colombia
• Chile
• Peru
• Venezuela

• And many more

  Extensive Industry Coverage

Tailored to Your Sector
We cater to a vast array of industries, ensuring that no matter your focus, our database has the coverage you need. Key industries include:

• Finance: Access to high-level contacts in banking, investment, and financial services.
• Manufacturing: Connect with decision-makers in production, logistics, and supply chain management.
• Technology: Engage with leaders in software, hardware, and IT services.
• Healthcare: Reach out to executives in hospitals, pharmaceuticals, and biotech.
• Retail: Identify key players in e-commerce, brick-and-mortar stores, and consumer goods.
• Hospitality: Connect with industry leaders in hotels, travel, and leisure.
• Energy: Tap into contacts within oil, gas, renewable energy, and utilities.

• Transportation: Engage with decision-makers in logistics, shipping, and infrastructure.

  Comprehensive Employee Size and Revenue Data

Insights Across Business Sizes
Our database doesn’t just provide contact information—it also includes detailed data on employee size and revenue. Whether you’re targeting small startups, mid-sized enterprises, or large multinational corporations, our database has the depth to accommodate your needs. We offer insights into:

• Employee Size: From small businesses with 1-10 employees to large enterprises with 10,000+ employees.

• Revenue Size: Covering companies ranging from early-stage startups to global giants in the Fortune 500.

  Empower Your Business with Unmatched Data Access

Unlock Opportunities Across the Americas
With the North America Data, you gain access to a powerful resource designed to unlock endless opportunities for growth and success. Whether you’re looking to break into new markets, establish strong business relationships, or enhance your market intelligence, our database equips you with the tools you need to excel.

Explore the North America Data tod...

Analysis of ‘Startup Success Prediction’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/manishkc06/startup-success-prediction on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

A startup or start-up is a company or project begun by an entrepreneur to seek, develop, and validate a scalable economic model. While entrepreneurship refers to all new businesses, including self-employment and businesses that never intend to become registered, startups refer to new businesses that intend to grow large beyond the solo founder. Startups face high uncertainty and have high rates of failure, but a minority of them do go on to be successful and influential. Some startups become unicorns: privately held startup companies valued at over US$1 billion. [Source of information: Wikipedia] https://images.unsplash.com/photo-1556761175-5973dc0f32e7?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=500&q=60" alt="startup image"> Startups play a major role in economic growth. They bring new ideas, spur innovation, create employment thereby moving the economy. There has been an exponential growth in startups over the past few years. Predicting the success of a startup allows investors to find companies that have the potential for rapid growth, thereby allowing them to be one step ahead of the competition.

Objective

The objective is to predict whether a startup which is currently operating turns into a success or a failure. The success of a company is defined as the event that gives the company's founders a large sum of money through the process of M&A (Merger and Acquisition) or an IPO (Initial Public Offering). A company would be considered as failed if it had to be shut down.

About the Data

The data contains industry trends, investment insights and individual company information. There are 48 columns/features. Some of the features are:

• age_first_funding_year – quantitative
• age_last_funding_year – quantitative
• relationships – quantitative
• funding_rounds – quantitative
• funding_total_usd – quantitative
• milestones – quantitative
• age_first_milestone_year – quantitative
• age_last_milestone_year – quantitative
• state – categorical
• industry_type – categorical
• has_VC – categorical
• has_angel – categorical
• has_roundA – categorical
• has_roundB – categorical
• has_roundC – categorical
• has_roundD – categorical
• avg_participants – quantitative
• is_top500 – categorical
• status(acquired/closed) – categorical (the target variable, if a startup is ‘acquired’ by some other organization, means the startup succeed)

Acknowledgements

• I would like to thank Ramkishan Panthena, for providing us this dataset. He is a Machine Learning Engineer at GMO.
• This dataset was used in data sprint #5 at DPhi.

Inspiration

Predicting the success of a startup allows investors to find companies that have the potential for rapid growth, thereby allowing them to be one step ahead of the competition.

--- Original source retains full ownership of the source dataset ---

Business Confidence in the United States decreased to 48.50 points in May from 48.70 points in April of 2025. This dataset provides the latest reported value for - United States ISM Purchasing Managers Index (PMI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This layer contains data on the number of employees and number of establishments for selected 2-digit North American Industry Classification System (NAICS) codes. This is shown by District boundaries. The full CBP data set (available at census.gov) is updated annually to contain the most currently released CBP data. Current Vintage: 2022CBP Table: CB2000CBPData downloaded from: Census Bureau's API for County Business Patterns Date of API call: January 3, 2025 The United States Census Bureau's County Business Patterns Program (CBP):About this ProgramDataTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census Bureau and CBP when using this data. Data Processing Notes:Boundaries come from the US Census Bureau TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census Bureau. These are Census Bureau boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Blank values represent industries where there either were no businesses in that industry and that geography OR industries where the data had to be withheld to avoid disclosing data for individual companies. Users should visit data.census.gov or Census Business Builder for more details on these withheld records.Data processed by the Office of Planning on R statistical software and ESRI ArcGIS Desktop.

This layer shows data on the number of establishments and revenue for select 2-digit North American Industry Classification System (NAICS) sectors and for NAICS 00, All Sectors. This is shown by county and state boundaries. The full NES data set (available at census.gov) is updated annually to contain the most currently released NES data, and contains estimates and measure of reliability. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Current Vintage: 2021NES Table: NS2100NESData downloaded from: Census Bureau's API for Nonemployer StatisticsDate of API call: March 22, 2024National Figures: data.census.govThe United States Census Bureau's Nonemployer Statistics Program (NES):About this ProgramDataTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census Bureau and NES when using this data.Data Processing Notes:Boundaries come from the US Census Bureau TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census Bureau. These are Census Bureau boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 51 records - all US states, Washington D.C..Blank values represent industries where there either were no businesses in that industry and that geography OR industries where the data had to be withheld to avoid disclosing data for individual companies. Users should visit data.census.gov or Census Business Builder for more details on these withheld records.Data shown in thousands of dollars are indicated by '($1000)' in the field aliasing. Average and Totals include NAICS 11.

Unlock the door to business expansion by investing in our real-time eCommerce leads list. Gain direct access to store owners and make informed decisions with data fields including Store Name, Website, Contact First Name, Contact Last Name, Email Address, Physical Address, City, State, Country, Zip Code, Phone Number, Revenue Size, Employee Size, and more on demand.

Ensure a lifetime of access for continuous growth and tailor your campaigns with accurate and reliable information, initiating targeted efforts that align with your marketing goals. Whether you're targeting specific industries or global locations, our database provides up-to-date and valuable insights to support your business journey.

• 4M+ eCommerce Companies • 40M+ Worldwide eCommerce Leads • Direct Contact Info for Shop Owners • 47+ eCommerce Platforms • 40+ Data Points • Lifetime Access • 10+ Data Segmentations • Sample Data

Discover the unparalleled potential of our comprehensive eCommerce leads database, featuring essential data fields such as Store Name, Website, Contact First Name, Contact Last Name, Email Address, Physical Address, City, State, Country, Zip Code, Phone Number, Revenue Size, Employee Size, and more on demand.

With a focus on Shopify, Amazon, eBay, and other global retail stores, this database equips you with accurate information for successful marketing campaigns. Supercharge your marketing efforts with our enriched contact and company database, providing real-time, verified data insights for strategic market assessments and effective buyer engagement across digital and traditional channels.

• 4M+ eCommerce Companies • 40M+ Worldwide eCommerce Leads • Direct Contact Info for Shop Owners • 47+ eCommerce Platforms • 40+ Data Points • Lifetime Access • 10+ Data Segmentations • Sample Data"

A comprehensive dataset of Green Card sponsorship trends, including data on employment-based Green Cards, labor certifications, top employers, and industry trends.