The Business Dynamics Statistics (BDS) includes measures of establishment openings and closings, firm startups, job creation and destruction by firm size, age, and industrial sector, and several other statistics on business dynamics. The U.S. economy is comprised of over 6 million establishments with paid employees. The population of these businesses is constantly churning -- some businesses grow, others decline and yet others close. New businesses are constantly replenishing this pool. The BDS series provide annual statistics on gross job gains and losses for the entire economy and by industrial sector, state, and MSA. These data track changes in employment at the establishment level, and thus provide a picture of the dynamics underlying aggregate net employment growth.

There is a longstanding interest in the contribution of small businesses to job and productivity growth in the U.S. Some recent research suggests that it is business age rather than size that is the critical factor. The BDS permits exploring the respective contributions of both firm age and size.

BDS is based on data going back through 1976. This allows business dynamics to be tracked, measured and analyzed for young firms in their first critical years as well as for more mature firms including those that are in the process of reinventing themselves in an ever changing economic environment.

If you need help understanding the terms used, check out these definitions.

Data Dictionary

Listing of All Active Business. The data displayed is based on the Principal Place of Business residing in Oregon only. The county was determined by a City-Zip combination.

CZ: Start-Up Procedures to Register a Business: Female data was reported at 9.000 Number in 2019. This stayed constant from the previous number of 9.000 Number for 2018. CZ: Start-Up Procedures to Register a Business: Female data is updated yearly, averaging 9.000 Number from Dec 2003 (Median) to 2019, with 17 observations. The data reached an all-time high of 10.000 Number in 2007 and a record low of 8.000 Number in 2017. CZ: Start-Up Procedures to Register a Business: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Czech Republic – Table CZ.World Bank.WDI: Company Statistics. Start-up procedures are those required to start a business, including interactions to obtain necessary permits and licenses and to complete all inscriptions, verifications, and notifications to start operations. Data are for businesses with specific characteristics of ownership, size, and type of production.;World Bank, Doing Business project (http://www.doingbusiness.org/). NOTE: Doing Business has been discontinued as of 9/16/2021. For more information: https://bit.ly/3CLCbme;Unweighted average;Data are presented for the survey year instead of publication year.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for master in business administration business statistics data analytics in the U.S.

This table contains 2736 series, with data starting from 2001 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) Business dynamics measure (16 items: Number of active employer businesses in the private sector; Number of entrants; Number of incumbents; Number of exits; ...) North American Industry Classification System (NAICS) (19 items: Private sector; Agriculture, forestry, fishing and hunting; Mining, quarrying, and oil and gas extraction; Utilities; ...) Firm size (9 items: Private sector; From 0 to less than 100 employees; From 0 to less than 50 employees; Less than 5 employees; ...).

This dataset presents statistics on: the number of establishments; sales, value of shipments, or revenue; annual payroll; and number of employees whose NAICS classification has changed between the current and the previous economic censuses. Data are shown for 6-digit current economic census NAICS industries and their 8-digit previous economic census NAICS components for the U.S. Includes only establishments of firms with paid employees.

ChatGPT, an artificial intelligence (AI) powered chatbot, is most used by companies in the technical and education industries, with over 200 companies using it in 2023. It is perhaps unsurprising that the technical field has embraced the use of ChatGPT, but it is interesting that so many educational institutes have begun to use it. While other industries do utilize the OpenAI-made chatbot, there are less than a 100 institutions and companies that use ChatGPT in other industries. This is especially true of agriculture, cultural, and legal industries, where only a single company is using ChatGPT in 2023.

Data collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data covers the period 2002-2023. It show business establishments with their business address, …Show full descriptionData collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data covers the period 2002-2023. It show business establishments with their business address, industry (ANZSIC4) classification, location and CLUE block and small area allocation. A business establishment is defined as a • Commercial occupant in a building • Separate land use • Any permanent presence of economic activity in accordance with standard Industry classification (ANZSIC). Hence, if one organisation has its presence in several buildings in the CLUE area, each time it will be counted as a separate establishment. Consequently, the count of establishments presented in CLUE represents the number of locations, rather than 'enterprises'. For more information about CLUE see http://www.melbourne.vic.gov.au/clue For more information about the ANZSIC industry classification system see http://www.abs.gov.au/ausstats/abs@.nsf/mf/1292.0

The dataset exists to observe the entrepreneurial activity of Austin over a long time period. The data comes from the U.S. Census County Business Pattern table and is capturing data at the Travis County level. It contains the cumulative count of firms by employee size and count of firms by employee size by industry. This data can be used to see changes of employer growth by industry; to project where workforce growth could be occurring; or to simply see how many small businesses there are in Austin.

View more details and insights related to this data set on the story page: data.austintexas.gov/stories/s/ndb5-si22

In 2023, there were estimated to be over 376.66 million companies operating worldwide, of which over 200 million were in Asia, 67 million were in Africa, and 34 million were in Europe.

Big Data and Business Analytics Market Outlook

In 2023, the global Big Data and Business Analytics market size is estimated to be valued at approximately $274 billion, and with a projected compound annual growth rate (CAGR) of 12.4%, it is anticipated to reach around $693 billion by 2032. This significant growth is driven by the escalating demand for data-driven decision-making processes across various industries, which leverage insights derived from vast data sets to enhance business efficiency, optimize operations, and drive innovation. The increasing adoption of Internet of Things (IoT) devices, coupled with the exponential growth of data generated daily, further propels the need for advanced analytics solutions to harness and interpret this information effectively.

A critical growth factor in the Big Data and Business Analytics market is the increasing reliance on data to gain a competitive edge. Organizations are now more than ever looking to uncover hidden patterns, correlations, and insights from the data they collect to make informed decisions. This trend is especially prominent in industries such as retail, where understanding consumer behavior can lead to personalized marketing strategies, and in healthcare, where data analytics can improve patient outcomes through precision medicine. Moreover, the integration of big data analytics with artificial intelligence and machine learning technologies is enabling more accurate predictions and real-time decision-making, further enhancing the value proposition of these analytics solutions.

Another key driver of market growth is the continuous technological advancements and innovations in data analytics tools and platforms. Companies are increasingly investing in advanced analytics capabilities, such as predictive analytics, prescriptive analytics, and real-time analytics, to gain deeper insights into their operations and market environments. The development of user-friendly and self-service analytics tools is also democratizing data access within organizations, empowering employees at all levels to leverage data in their daily decision-making processes. This democratization of data analytics is reducing the reliance on specialized data scientists, thereby accelerating the adoption of big data analytics across various business functions.

The increasing emphasis on regulatory compliance and data privacy is also driving growth in the Big Data and Business Analytics market. Strict regulations, such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States, require organizations to manage and analyze data responsibly. This is prompting businesses to invest in robust analytics solutions that not only help them comply with these regulations but also ensure data integrity and security. Additionally, as data breaches and cybersecurity threats continue to rise, organizations are turning to analytics solutions to identify potential vulnerabilities and mitigate risks effectively.

Regionally, North America remains a dominant player in the Big Data and Business Analytics market, benefiting from the presence of major technology companies and a high rate of digital adoption. The Asia Pacific region, however, is emerging as a significant growth area, driven by rapid industrialization, urbanization, and increasing investments in digital transformation initiatives. Europe also showcases a robust market, fueled by stringent data protection regulations and a strong focus on innovation. Meanwhile, the markets in Latin America and the Middle East & Africa are gradually gaining momentum as organizations in these regions are increasingly recognizing the value of data analytics in enhancing business outcomes and driving economic growth.

Component Analysis

The Big Data and Business Analytics market is segmented by components into software, services, and hardware, each playing a crucial role in the ecosystem. Software components, which include data management and analytics tools, are at the forefront, offering solutions that facilitate the collection, analysis, and visualization of large data sets. The software segment is driven by a demand for scalable solutions that can handle the increasing volume, velocity, and variety of data. As organizations strive to become more data-centric, there is a growing need for advanced analytics software that can provide actionable insights from complex data sets, leading to enhanced decision-making capabilities.

In the services segment, businesses are increasingly seeking consultation, implementation, and support services to effective

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

HU: New Business Density: New Registrations per 1000 People Aged 15 to 64 data was reported at 3.382 Number in 2016. This records an increase from the previous number of 3.162 Number for 2015. HU: New Business Density: New Registrations per 1000 People Aged 15 to 64 data is updated yearly, averaging 4.184 Number from Dec 2006 (Median) to 2016, with 11 observations. The data reached an all-time high of 7.644 Number in 2011 and a record low of 3.162 Number in 2015. HU: 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 Hungary – Table HU.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.

Business demography statistics

Business demography statistics provide an annual snapshot (as at February) of the structure and characteristics of New Zealand businesses. Statistics produced include counts of enterprises and geographic units by industry, geography such as region or statistical area 2 (SA2), institutional sector, business type, degree of overseas ownership, enterprise births, enterprise deaths, survival rate of enterprises and employment levels.

The series covers economically significant private-sector and public-sector enterprises that are engaged in the production of goods and services in New Zealand. These enterprises are maintained on the Statistics NZ Business Register (BR), which generally includes all employing units and those enterprises with GST turnover greater than $30,000 per year.

For further information: https://www.stats.govt.nz/information-releases/new-zealand-business-demography-statistics-at-february-2020

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Statistical geography

This dataset provides data for the SA2 geography (SA22020_V1_00). Names are provided with and without tohutō/macrons. The name field without macrons is suffixed ‘ascii’. Data for earlier years is available in NZ.Stat– see Geographic units by industry and statistical area 2000-2020.

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Geographic units

The geographic unit represents a business location engaged in one, or predominantly one, kind of economic activity at a single physical site or base (e.g. a factory, a farm, a shop, an office). Geographic units are unique to enterprises and an enterprise unit can have one or many geographic units (business locations). Typically, an enterprise unit only has a single geographic unit, unless the enterprise has paid employees who permanently work at more than one location. Geographic units can be transferred between enterprises (e.g. enterprise B purchases a factory (a geographic unit on the BR) as a going concern from enterprise A).

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Employee count data

Employee counts (ECs) are sourced from the Inland Revenue employer monthly schedule (EMS) tax form.

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Industry

The Australian and New Zealand Standard Industrial Classification (ANZSIC) 2006 is used to compile Business Demography statistics. The classification can be viewed and downloaded from Ariā.

ANZSIC 2006 divisions are:

A Agriculture, Forestry and Fishing

B Mining

C Manufacturing

D Electricity, Gas, Water and Waste Services

E Construction

F Wholesale Trade

G Retail Trade

H Accommodation and Food Services

I Transport, Postal and Warehousing

J Information Media and Telecommunications

K Financial and Insurance Services

L Rental, Hiring and Real Estate Services

M Professional, Scientific and Technical Services

N Administrative and Support Services

O Public Administration and Safety

P Education and Training

Q Health Care and Social Assistance

R Arts and Recreation Services

S Other Services

Total Industry

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Rounding

Enterprise, geographic unit, and EC counts are randomly rounded. Due to rounding, individual figures may not sum to the published totals.

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Quality limitations of fine-level data, including SA2-level data

We recommend caution when using fine-level regional and industry business demography data. The Business Register (BR) supports quality national-level and aggregate industry-level statistics but is not designed to provide quality fine-level regional or industry statistics. The BR update sources can have timing lags and less robust information for small and medium-sized enterprises. These quality weaknesses can be highlighted in fine-level business demography statistics.

For more information about data quality and available data go to DataInfo+.

Basic data by kind-of-activity unit according to Structural Business Statistics by industrial classification (NACE Rev. 2), observations and year

With 1.3 Million Businesses in Finland , Techsalerator has access to the highest B2B count of Data/Business Data in the country.

Thanks to our unique tools and large data specialist team, we can select the ideal targeted dataset based on the unique elements such as sales volume of a company, the company's location, no. of employees etc...

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Province of Nyland and Tavastehus Uudenmaan ja Hämeen lääni Nylands och Tavastehus län Helsinki / Hämeenlinna

Province of Ostrobothnia Pohjanmaan lääni Österbottens län Oulu / Vaasa

Province of Viborg and Nyslott Viipurin ja Savonlinnan lääni Viborgs och Nyslotts län Vyborg

Province of Kexholm Käkisalmen lääni Kexholms län Kexholm

Province of Kymmenegård and Nyslott Savonlinnan ja Kymenkartanon lääni Kymmenegårds och Nyslotts län Lappeenranta

Province of Savolax and Kymmenegård Kymenkartanon ja Savon lääni Savolax och Kymmenegårds län Loviisa

Province of Vaasa Vaasan lääni Vasa län Vaasa

Province of Oulu Oulun lääni Uleåborgs län Oulu

Province of Kymmenegård Kymenkartanon lääni Kymmenegårds län Heinola

Province of Savolax and Karelia Savon ja Karjalan lääni Savolax och Karelens län Kuopio

Province of Viipuri Viipurin lääni Viborgs län Vyborg

Province of Uusimaa Uudenmaan lääni Nylands län Helsinki

Province of Häme Hämeen lääni Tavastehus län Hämeenlinna

Province of Mikkeli Mikkelin lääni St. Michels län Mikkeli

Province of Kuopio Kuopion lääni Kuopio län Kuopio

Province of Åland Ahvenanmaan lääni Ålands län Mariehamn

Province of Petsamo Petsamon lääni Petsamo län Pechenga

Province of Lapland Lapin lääni Lapplands län Rovaniemi

Province of Kymi Kymen lääni Kymmene län Kouvola

Province of Central Finland Keski-Suomen lääni Mellersta Finlands län Jyväskylä

Province of North Karelia Pohjois-Karjalan lääni Norra Karelens län Joensuu

Province of Southern Finland Etelä-Suomen lääni Södra Finlands län Hämeenlinna

Province of Western Finland Länsi-Suomen lääni Västra Finlands län Turku

Province of Eastern Finland Itä-Suomen lääni Östra Finlands län Mikkeli

Number of businesses in routes of 1 000 m x 1 000 m as of 01 January. The breakdown indicates the total number of businesses in the routes. Historical versions back to 2013.

Summary statistics of business dynamism taken from the Longitudinal Business Database (LBD), UK.

MA: Firms using Banks to Finance Investment: % of Firms data was reported at 34.800 % in 2013. This records an increase from the previous number of 12.300 % for 2007. MA: Firms using Banks to Finance Investment: % of Firms data is updated yearly, averaging 23.550 % from Dec 2007 (Median) to 2013, with 2 observations. The data reached an all-time high of 34.800 % in 2013 and a record low of 12.300 % in 2007. MA: Firms using Banks to Finance Investment: % of Firms data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Company Statistics. Firms using banks to finance investment are the percentage of firms using banks to finance investments.; ; World Bank, Enterprise Surveys (http://www.enterprisesurveys.org/).; Unweighted average;

Here are some small business statistics on how they are generally financed.