Release Date: 2017-07-13.[NOTE: Includes firms with payroll at any time during 2015. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2015 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status or that were publicly held or not classifiable by gender, ethnicity, race, or veteran status. Percentages are for respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms by Decision Making for Sales and Purchases Activities by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015. ..Release Schedule. . This file was released in July 2017.. ..Key Table Information. . These data are related to all other 2015 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2015 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2015 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. In this file, "respondent firms" refers to all firms that reported gender, ethnicity, race, or veteran status for at least one owner or returned a survey form with at least one item completed and were publicly held or not classifiable by gender, ethnicity, race, and veteran status.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms by Decision Making for Sales and Purchases Activities by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. Percent of respondent firms with paid employees. Percent of sales and receipts of respondent firms with paid employees. Percent of number of employees of respondent firms with paid employees. Percent of annual payroll of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of respondent firms. . All firms. Female-owned. Male-owned. Equally male-/female-owned. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. All firms classifiable by gender, ethnicity, race, and veteran status. Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 ...

County Business Patterns (CBP) is an annual series that provides sub-national economic data by industry. This series includes the number of establishments, employment during the week of March 12, first quarter payroll, and annual payroll. This data is useful for studying the economic activity of small areas, analyzing economic changes over time, and as a benchmark for other statistical series, surveys, and databases between economic censuses. Businesses use the data for analyzing market potential, measuring the effectiveness of sales and advertising programs, setting sales quotas, and developing budgets. Government agencies use the data for administration and planning.

This statistic displays the business creation benefits as a result of Big Data in the United Kingdom (UK) from 2015 to 2020, by industry. It was estimated that the professional service sector would benefit most from business creation due to Big Data. Healthcare was the second ranked sector with expected gains of roughly *** billion British pounds.

This data series is a monthly count of enterprises as at the end of each month, mostly sourced from administrative data. This data is different from the annually published Business demography statistics which is based on internationally recommended methodology.

This statistic displays the business innovation benefits as a result of Big Data in the United Kingdom (UK) from 2015 to 2020, by industry. It was estimated that the manufacturing sector would benefit most from business innovation due to Big Data. Telecommunications was the second ranked single sector with expected gains of roughly **** billion British pounds.

The statistic shows the leading benefits of business intelligence and data analytics to business organizations in the United States, according to a 2015 survey conducted by the Harvard Business Review Analytics Service. As of 2015, ** percent of respondents felt that the ability to access data any time, anywhere was an important benefit of business intelligence and data analytics to their organization.

Samoa WS: New Business Density: New Registrations per 1000 People Aged 15 to 64 data was reported at 1.012 Number in 2016. This records a decrease from the previous number of 1.221 Number for 2015. Samoa WS: New Business Density: New Registrations per 1000 People Aged 15 to 64 data is updated yearly, averaging 1.012 Number from Dec 2006 (Median) to 2016, with 11 observations. The data reached an all-time high of 1.221 Number in 2015 and a record low of 0.392 Number in 2007. Samoa WS: New Business Density: New Registrations per 1000 People Aged 15 to 64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Samoa – Table WS.World Bank.WDI: Businesses Registered Statistics. New businesses registered are the number of new limited liability corporations registered in the calendar year.; ; World Bank's Entrepreneurship Survey and database (http://www.doingbusiness.org/data/exploretopics/entrepreneurship).; Unweighted average; For cross-country comparability, only limited liability corporations that operate in the formal sector are included.

Mexico MX: New Businesses Registered data was reported at 45,256.000 Number in 2016. This records a decrease from the previous number of 46,174.000 Number for 2015. Mexico MX: New Businesses Registered data is updated yearly, averaging 42,562.000 Number from Dec 2006 (Median) to 2016, with 11 observations. The data reached an all-time high of 46,174.000 Number in 2015 and a record low of 22,116.000 Number in 2006. Mexico MX: New Businesses Registered data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Businesses Registered Statistics. New businesses registered are the number of new limited liability corporations registered in the calendar year.; ; World Bank's Entrepreneurship Survey and database (http://www.doingbusiness.org/data/exploretopics/entrepreneurship).; ; For cross-country comparability, only limited liability corporations that operate in the formal sector are included.

The statistic shows the constant annual growth rate of the fastest growing big data and analytics categories worldwide, between 2015 and 2020. In that period, the market for non-relational analytics data stores is projected to grow by **** percent.

Mauritania MR: New Business Density: New Registrations per 1000 People Aged 15 to 64 data was reported at 0.495 Number in 2016. This records an increase from the previous number of 0.092 Number for 2015. Mauritania MR: New Business Density: New Registrations per 1000 People Aged 15 to 64 data is updated yearly, averaging 0.294 Number from Dec 2015 (Median) to 2016, with 2 observations. The data reached an all-time high of 0.495 Number in 2016 and a record low of 0.092 Number in 2015. Mauritania MR: New Business Density: New Registrations per 1000 People Aged 15 to 64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mauritania – Table MR.World Bank: Businesses Registered Statistics. New businesses registered are the number of new limited liability corporations registered in the calendar year.; ; World Bank's Entrepreneurship Survey and database (http://www.doingbusiness.org/data/exploretopics/entrepreneurship).; Unweighted average; For cross-country comparability, only limited liability corporations that operate in the formal sector are included.

The global big data and business analytics (BDA) market was valued at 168.8 billion U.S. dollars in 2018 and is forecast to grow to 215.7 billion U.S. dollars by 2021. In 2021, more than half of BDA spending will go towards services. IT services is projected to make up around 85 billion U.S. dollars, and business services will account for the remainder. Big data High volume, high velocity and high variety: one or more of these characteristics is used to define big data, the kind of data sets that are too large or too complex for traditional data processing applications. Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets. For example, connected IoT devices are projected to generate 79.4 ZBs of data in 2025. Business analytics Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate business insights. The size of the business intelligence and analytics software application market is forecast to reach around 16.5 billion U.S. dollars in 2022. Growth in this market is driven by a focus on digital transformation, a demand for data visualization dashboards, and an increased adoption of cloud.

Learn more about Mayor Garcetti's Great Streets Initiative here http://lagreatstreets.org/ Survey was taken May-June 2015.

Release Date: 2017-07-13.[NOTE: Includes firms with payroll at any time during 2015. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2015 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status or that were publicly held or not classifiable by gender, ethnicity, race, or veteran status. Percentages are for respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms That Operated as Franchises or Partially as Franchises by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015. ..Release Schedule. . This file was released in July 2017.. ..Key Table Information. . These data are related to all other 2015 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2015 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2015 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. In this file, "respondent firms" refers to all firms that reported gender, ethnicity, race, or veteran status for at least one owner or returned a survey form with at least one item completed and were publicly held or not classifiable by gender, ethnicity, race, and veteran status.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms That Operated as Franchises or Partially as Franchises by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. Percent of respondent firms with paid employees. Percent of sales and receipts of respondent firms with paid employees. Percent of number of employees of respondent firms with paid employees. Percent of annual payroll of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of respondent firms. . All firms. Female-owned. Male-owned. Equally male-/female-owned. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. All firms classifiable by gender, ethnicity, race, and veteran status. Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 1...

In the third quarter of the 2025 fiscal year, Microsoft generated approximately ***** billion U.S. dollars of operating income from productivity and business processes, an increase of over ***** billion U.S. dollars compared to the same quarter in the previous year.

UK estimates of annual research and development (R&D) spending by UK businesses.

Turkey TR: New Business Density: New Registrations per 1000 People Aged 15 to 64 data was reported at 1.178 Number in 2016. This records a decrease from the previous number of 1.250 Number for 2015. Turkey TR: New Business Density: New Registrations per 1000 People Aged 15 to 64 data is updated yearly, averaging 1.055 Number from Dec 2006 (Median) to 2016, with 11 observations. The data reached an all-time high of 1.250 Number in 2015 and a record low of 0.786 Number in 2012. Turkey TR: New Business Density: New Registrations per 1000 People Aged 15 to 64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank.WDI: Businesses Registered Statistics. New businesses registered are the number of new limited liability corporations registered in the calendar year.; ; World Bank's Entrepreneurship Survey and database (http://www.doingbusiness.org/data/exploretopics/entrepreneurship).; Unweighted average; For cross-country comparability, only limited liability corporations that operate in the formal sector are included.

Small Business Sentiment in the United States increased to 51.67 in February from 49.03 in January of 2015. This dataset provides the latest reported value for - US Small Business Health Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Longitudinal Small Business Survey (LSBS) is a large-scale telephone survey of small business owners and managers commissioned by the Department for Business and Trade (DBT). This survey is the latest in a series of annual and biennial Small Business Surveys (SBS) dating back to 2003.

In 2015, the survey methodology changed to include a longitudinal tracking element. A large sample size was recruited in Year One (2015) to establish a panel of businesses to be re-surveyed in subsequent years. This will allow a detailed analysis of how combinations of factors affect business performance.

The LSBS is intended to:

• Improve the understanding of what drives and constrains business performance and growth by addressing evidence gaps relating to the lags between many business activities and associated performance outcomes;
• Provide improved data on current business performance and the factors that affect this. The larger survey size will provide more reliable findings for key sub-groups of the business population and in relation to activities such as seeking finance, which are only relevant to part of the sample.

The data available covers all respondents over the course of the six years so far. Further information and research reports are available on the GOV.UK "https://www.gov.uk/government/collections/small-business-survey-reports"> Small Business Survey Reports webpage.

Controlled (Secure) Access Version
A Controlled (Secure) Access version of the LSBS is available from the UK Data Archive, subject to stringent secure access conditions. Extra variables include postcode district, 2-, 3-, and 4-digit SIC codes; and Inter-Departmental Business Register (IDBR) reference numbers for linking to other business surveys. Small Business Survey data files for 2010 and 2012 containing 4-digit SIC codes and IDBR reference numbers are available under SN 6856. Users are strongly advised to check whether the safeguarded version is sufficient for their needs before considering an application for the Controlled (Secure) Access version.

Latest edition information
For the ninth edition (December 2024), the data and documentation have been updated to include Year 9 of the survey, completed during 2023-2024.

Historical Dataset of Entrepreneur High School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2015-2023),Total Classroom Teachers Trends Over Years (2015-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2015-2023),American Indian Student Percentage Comparison Over Years (2019-2023),Asian Student Percentage Comparison Over Years (2015-2023),Hispanic Student Percentage Comparison Over Years (2015-2023),Black Student Percentage Comparison Over Years (2015-2023),White Student Percentage Comparison Over Years (2015-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Diversity Score Comparison Over Years (2015-2023)