The number of persons employed by businesses (both for-profit and non-profit) that provide products and services to local residents. The industries included in this indicator are: Retail Trade (NAICS 44-45); Finance and Insurance (NAICS 52); Professional, Scientific, and Technical Services (NAICS 54); Health Care and Social Assistance (NAICS 62); Arts, Entertainment, and Recreation (NAICS 71); Accommodation and Food Services (NAICS 72); and Other Services except Public Administration (NAICS 81). The primary industry reported by each business was used to determine their inclusion. The persons employed by these businesses may not necessarily live in the neighborhood where the business is located. Source: InfoUSA Years Available: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

Historical information about the total Employees and Businesses Dataset is a snapshot of the total number of businesses that are currently in Mesa, as well as the total number of employees that work in Mesa. Source: ESRI Community Analyst. It is important to note that in this dataset, a “Full-Time Employee (FTE)” in Mesa is someone who may not necessarily live in Mesa, however, they are employed at a business that is located in Mesa. This is a distinct difference between the “Employment” number in Mesa, which is stated in the “Employment Dataset.” Employment refers to the total number of Mesa residents that are employed, within or outside of the City of Mesa.

Database file was created to support The Office of Economic Development ArcGIS.com application and to use in conjunction with ESRI Business Online Analyst. The data was provided by Data Axle in February 2023. The purpose of the map is to view business data in relation to local zoning and land use, aerial photography, and relevant demographic data.By mining multiple data sources, Data Axle delivers a database that is that is the most robust and comprehensive available. We compile our databases from a number of sources including: GIS projects require the use of comprehensive data sets in order to perform a detailed analysis. Data Axle is widely recognized as providing the most comprehensive solution in the market – with more than 160+ business data elements to select from. A sample listing of the type of attributes collected are listed below.• Hundreds of county-level public sources, publications of record and Secretaries of State for new business registrations• Utility connects and disconnects nationwide• Industry & tourism directories• User generated feedback• Postal processing (NCOALink®, DPV®, LACSLink®, DSF®)• 4,000+ U.S. Yellow and White Page directories• Business name• Full address (Location, mailing, and landmark)• Type of business (Yellow Page heading, SIC and NAICS codes)• ZIP Code™ (including ZIP + 4®)• Telephone number• Fax number (where available)• Website addresses• Number of employees• Sales volume• Name, title, and gender of key executives• Franchise and brand information• Year the business was established• Headquarters, branch, and subsidiary information• Stock exchange and ticker symbol• Latitude, longitude and parcel-level geocodes• News headlines• UCC filings and bankruptcy notices (where available)• Square footage of business campus

This layer contains data on the number of employees and the number of establishments for selected 2-digit North American Industry Classification System (NAICS) codes from the the United States Census Bureau's County Business Patterns Program (CBP). 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. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Current Vintage: 2022 CBP Table: CB2000CBP. Data downloaded from: Census Bureau's API for County Business Patterns. Date of API call: January 2, 2025. 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. Downloaded data processed by the Office of Planning on R statistical software and ESRI ArcGIS Desktop. 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 for details on these withheld records.

The Regional Municipality of Durham, Planning and Economic Development Department and its municipal partners conduct an annual count of businesses within the Region. Between May and September, the Region's Business Count team visit every business establishment in Durham to gather basic information about the type and nature of the business, the number of employees, floor space, etc. The success of this important survey depends upon the assistance and co-operating of the region's business community.

HUBZone is a United States Small Business Administration (SBA) program for small companies that operate and employ people in Historically Underutilized Business Zones (HUBZones). The HUBZone program was created in response to the HUBZone Empowerment Act created by the US Congress in 1998.[1] Based on the Act, small businesses will be designated as HUBZone certified if they have the following criteria:The firm must be a small business based on the North American Industry Classification System (NAICS)[2] for size standards.The business must be at least 51% owned and controlled by U.S. citizens, or a Community Development Corporation, an agricultural cooperative, or an Indian tribe (including Alaska Native Corporations).[3]The firm's principal office (the location where the greatest number of employees perform their work, excluding contract sites) must be in a HUBZone.35% of the firms total workforce must reside in a HUBZone.

This is a collection of layers created by Tian Xie(Intern in DDP) in August, 2018. This collection includes Detroit Parcel Data(Parcel_collector), InfoUSA business data(BIZ_INFOUSA), and building data(Building). The building and business data have been edited by Tian during field research and have attached images.

This is a collection of layers created by Tian Xie(Intern in DDP) in August, 2018. This collection includes Detroit Parcel Data(Parcel_collector), InfoUSA business data(BIZ_INFOUSA), and building data(Building). The building and business data have been edited by Tian during field research and have attached images.

Data Source: The primary data source used for this analysis are point-level business establishment data from InfoUSA. This commercial database produced by InfoGroup provides a comprehensive list of businesses in the SCAG region, including their industrial classification, number of employees, and several additional fields. Data have been post-processed for accuracy by SCAG staff and have an effective date of 2016. Locally-weighted regression: First, the SCAG region is overlaid with a grid, or fishnet, of 1km, 2km, and ½-km per cell. At the 1km cell size, there are 16,959 cells covering the SCAG region. Using the Spatial Join feature in ArcGIS, a sum total of business establishments and total employees (i.e., not separated by industrial classification) were joined to each grid cell. Note that since cells are of a standard size, the employment total in a cell is the equivalent of the employment density. A locally-weighted regression (LWR) procedure was developed using the R Statistical Software package in order to identify subcenters.The below procedure is described for 1km grid cells, but was repeated for 2km and 1/2km cells. Identify local maxima candidates.Using R’s lwr package, each cell’s 120 nearest neighbors, corresponding to roughly 5.5 km in each direction, was explored to identify high outliers or local maxima based on the total employment field. Cells with a z-score of above 2.58 were considered local maxima candidates.Identify local maxima. LWR can result in local maxima existing within close proximity. This step used a .dbf-format spatial weights matrix (knn=120 nearest neighbors) to identify only cells which are higher than all of their 120 nearest neighbors. At the 1km scale, 84 local maxima were found, which will form the “peak” of each individual subcenter. Search adjacent cells to include as part of each subcenter. In order to find which cells also are part of each local maximum’s subcenter, we use a queen (adjacency) contiguity matrix to search adjacent cells up to 120 nearest neighbors, adding cells if they are also greater than the average density in their neighborhood. A total of 695 cells comprise subcenters at the 1km scale. A video from Kane et al. (2018) demonstrates the above aspects of the methodology (please refer to 0:35 through 2:35 of https://youtu.be/ylTWnvCCO54), with several minor differences which result in a different final map of subcenters: different years and slightly different post-processing steps for InfoUSAdata, video study covers 5-county region (Imperial county not included), and limited to 1km scale subcenters.A challenge arises in that using 1km grid cells may fail to identify the correct local maximum for a particularly large employment center whose experience of high density occurs over a larger area. The process was repeated at a 2km scale, resulting in 54 “coarse scaled” subcenters. Similarly, some centers may exist with a particularly tightly-packed area of dense employment which is not detectable at the medium, 1km scale. The process was repeated again with ½-km grid cells, resulting in 95 “fine scaled” subcenters. In many instances, boundaries of fine, medium, and coarse scaled subcenters were similar, but differences existed. The next step was to qualitatively comparing results at each scale to create the final map of 72 job centers across the region. Most centers are medium scale, but some known areas of especially employment density were better captured at the 2km scale while . Giuliano and Small’s (1991) “ten jobs per acre” threshold was used as a rough guide to test for reasonableness when choosing a larger or smaller scale. For example, in some instances, a 1km scale included much additional land which reduced job density well below 10 jobs per acre. In this instance, an overlapping or nearby 1/2km scaled center provided a better reflection of the local employment peak. Ultimately, the goal was to identify areas where job density is distinct from nearby areas. Finally, in order to serve land use and travel demand modeling purposes for Connect SoCal, job centers were joined to their nearest TAZ boundaries. While the identification mechanism described above uses a combination of point and grid cell boundaries, the job centers boundaries expressed in this layer, and used for Connect SoCal purposes, are built from TAZ geographies. In Connect SoCal, job centers are associated with one of three strategies: focused growth, coworking space, or parking/AVR.Data Field/Value description:name: Name of job center based on name of local jurisdiction(s) or other discernable feature.Focused_Gr: Indicates whether job center was used for the 2020 RTP/SCS Focused Growth strategy, 1: center was used, 0: center was not used.Cowork: Indicates whether job center was used for the 2020 RTP/SCS Co-working space strategy, 1: center was used, 0: center was not used.Park_AVR: Indicates whether job center was used for the 2020 RTP/SCS parking and average vehicle ridership (AVR) strategies, 1: center was used, 0: center was not used. nTAZ: number of Transportation Analysis Zones (TAZs) which comprise this center.emp16: Estimated number of workers within job center boundaries based on 2016 InfoUSA point-based business establishment data. Values are rounded to the nearest 1000. acres: Land area within job center boundaries based on grid-based identification mechanism (i.e., not based on TAZ boundaries shown). Values are rounded to the nearest 100.

STATENT provides an overview of the economic landscape in Switzerland. Information is based on the number of companies, number of workplaces, number of employees, as well as data from company surveys.STATENT includes all companies and persons listed in the AHV register above a yearly threshold income of 2300 Swiss francs. This figure corresponds to the annual income from which employees in 2019 were compulsorily obliged to make AHV contributions. For each census, approx. 600 characteristics of enterprises and employees according to the General Classification of Economic Activity (NOGA 2008) are stored on an aggregate basis.For data protection reasons, absolute values from 1 to 4 cannot be given in standard evaluations and are therefore indicated in this data set as a class with the value «4».The service is in the Swiss coordinate system CH1903+ LV95. The LV95 Swiss Topographic map is best suited as a basemap for this service.

This map shows which areas have concentrations of high risk businesses in the event of an economic downturn. Areas in red have a higher concentration of one or more of the five categories (by NAICS code): Clothing/Accessory stores, General Merchandise stores, Arts/Entertainment/Recreation, Accommodation, and Food Service/Drinking Places. The popup breaks down count of businesses per category and percent of businesses for the area. Data is 2019 vintage and available by county, tract, and block group. Overall, in the US, these 5 categories make up 11.8% of total businesses.Esri's Business Summary Data: Esri's Business Locations data is extracted from a comprehensive list of businesses licensed from Infogroup. It summarizes the comprehensive list of businesses from Infogroup for select NAICS and SIC summary categories by geography and includes total number of businesses, total sales, and total number of employees for a trade area.Esri's U.S. 2019 Data: Population, age, income, race, home value, spending, business, and market potential are among the topics included in the data suite. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies. To browse, all data variables available within Esri's demographics explore the Data Browser. Additional Esri Resources:Get StartedEsri DemographicsU.S. 2019 Esri Updated DemographicsBusiness Summary DataMethodologies

This map shows which areas have concentrations of high risk businesses and potential loss of sales revenue in the event of an economic downturn. Areas in yellow have a higher concentration of sales revenue in one or more of the five categories (by NAICS code): Clothing/Accessory stores, General Merchandise stores, Arts/Entertainment/Recreation, Accommodation, and Food Service/Drinking Places. The popup breaks down total sales revenue by area, sales revenue as a percentage of total by area, percent of businesses for the area, and sales revenue by category. Data is 2019 vintage and available by county, tract, and block group. Overall, in the US, these 5 categories make up 7.11% of total sales revenue.Esri's Business Summary Data: Esri's Business Locations data is extracted from a comprehensive list of businesses licensed from Infogroup. It summarizes the comprehensive list of businesses from Infogroup for select NAICS and SIC summary categories by geography and includes total number of businesses, total sales, and total number of employees for a trade area.Esri's U.S. 2019 Data: Population, age, income, race, home value, spending, business, and market potential are among the topics included in the data suite. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies. To browse, all data variables available within Esri's demographics explore the Data Browser. Additional Esri Resources:Get StartedEsri DemographicsU.S. 2019 Esri Updated DemographicsBusiness Summary DataMethodologies

Insets displays an interactive collection of noncontiguous locations from a map within a single layout. Choose between two app modes for how insets are defined by picking from a list of predefined geographic layouts or customize the inset locations using bookmarks from the map or creating insets manually. Apply theming to inset windows and determine their position in the layout.Examples:View infectious disease rate information across all 50 US states and make visual comparisonsCreate an app showing traffic impact of railway crossing locations for a new transit line proposalVisualize commute times for employees of all district offices compared to those at company headquartersData RequirementsThis app has no data requirements.Key App CapabilitiesPredefined layout - Choose from a list of predefined geographic layouts to display insetsImport bookmarks - Use bookmarks from the webmap to automatically create insetsCreate new inset - Define new insets from scratch within the configurationPosition manager - Determine the position of custom insets and map widgets within the app layoutInset style - Control the size and color of inset outlines and apply a drop shadow effectPrint - Export an image of the map to PDFLanguage switcher - Publish a multilingual app that combines your translated custom text and the UI translations for supported languagesHome, Zoom Controls, Legend, SearchSupportabilityThis web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

This dataset represents the entire Industrial PinPointer database of manufacturing companies. Only those locations primarily engaged in manufacturing (SIC Codes 2000-3999) or those that are headquarters of manufacturing companies are included. This dataset covers manufacturing locations in the State of Alabama. Homeland SecurityThis dataset includes the entire Industrial PinPointer database of manufacturing companies, which includes the 2009 D2 of 2 update. 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. 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.Metadata

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 layer contains data on the number of establishments, total employment, and total annual payroll for for 20 selected 4- and 5-digit North American Industry Classification System (NAICS) codes. This is shown by county and state boundaries. The full CBP data set (available at census.gov) is updated annually to contain the most currently released CBP data. This layer is symbolized to show the total number of establishments depicted by size, and the average annual pay per employee, depicted by color.

Current Vintage: 2017

CBP Table: CB1700CBP

Data downloaded from: Census Bureau's API for County Business Patterns

Date of API call: June 1, 2019

The United States Census Bureau's County Business Patterns Program (CBP):

About this Program Data Technical Documentation News & Updates

This 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). The States layer contains 56 records - all US states, Washington D.C., Puerto Rico, and U.S. Island Areas 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.

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: 2020CBP Table: CB2000CBPData downloaded from: Census Bureau's API for County Business Patterns Date of API call: January 11, 2023 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 contains data on the number of establishments, total employment, and total annual payroll for for 20 selected 4- and 5-digit North American Industry Classification System (NAICS) codes. This is shown by county and state boundaries. The full CBP data set (available at census.gov) is updated annually to contain the most currently released CBP data. This layer is symbolized to show the total number of establishments depicted by size, and the average annual pay per employee, depicted by color.

Current Vintage: 2017

CBP Table: CB1700CBP

Data downloaded from: Census Bureau's API for County Business Patterns

Date of API call: June 1, 2019

The United States Census Bureau's County Business Patterns Program (CBP):

About this Program Data Technical Documentation News & Updates

This 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). The States layer contains 56 records - all US states, Washington D.C., Puerto Rico, and U.S. Island Areas 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.

This dataset has been published by the Commissioner of Revenue of the City of Virginia Beach and data.vbgov.com. The mission of data.vbgov.com is to provide timely and accurate City information to increase government transparency and access to useful and well organized data by the general public, non-governmental organizations, and City of Virginia Beach employees.

The government limits competition for certain contracts to businesses in historically underutilized business zones. It also gives preferential consideration to those businesses in full and open competition.Joining the HUBZone program makes your business eligible to compete for the program’s set-aside contracts. HUBZone-certified businesses also get a 10% price evaluation preference in full and open contract competitions.HUBZone-certified businesses can still compete for contract awards under other socio-economic programs they qualify for.Requirements:Be a small business according to SBA size standardsBe at least 51% owned and controlled by U.S. citizens, a Community Development Corporation, an agricultural cooperative, an Alaska Native corporation, a Native Hawaiian organization, or an Indian tribeHave its principal office located in a HUBZoneHave at least 35% of its employees living in a HUBZone