This statistic shows the types of data that organizations protect by using data backups worldwide as of 2019. Around 91 percent of respondents stated that they used backups to protect their business' databases, while only 16 percent stated that they used backups to protect their SaaS data.

Graph and download economic data for Business Applications for New Mexico (BUSAPPWNSANM) from 2006-01-07 to 2025-03-01 about business applications, NM, business, and USA.

Company Datasets for valuable business insights!

Discover new business prospects, identify investment opportunities, track competitor performance, and streamline your sales efforts with comprehensive Company Datasets.

These datasets are sourced from top industry providers, ensuring you have access to high-quality information:

• Owler: Gain valuable business insights and competitive intelligence. -AngelList: Receive fresh startup data transformed into actionable insights. -CrunchBase: Access clean, parsed, and ready-to-use business data from private and public companies. -Craft.co: Make data-informed business decisions with Craft.co's company datasets. -Product Hunt: Harness the Product Hunt dataset, a leader in curating the best new products.

We provide fresh and ready-to-use company data, eliminating the need for complex scraping and parsing. Our data includes crucial details such as:

• Company name;
• Size;
• Founding date;
• Location;
• Industry;
• Revenue;
• Employee count;
• Competitors.

You can choose your preferred data delivery method, including various storage options, delivery frequency, and input/output formats.

Receive datasets in CSV, JSON, and other formats, with storage options like AWS S3 and Google Cloud Storage. Opt for one-time, monthly, quarterly, or bi-annual data delivery.

With Oxylabs Datasets, you can count on:

• Fresh and accurate data collected and parsed by our expert web scraping team.
• Time and resource savings, allowing you to focus on data analysis and achieving your business goals.
• A customized approach tailored to your specific business needs.
• Legal compliance in line with GDPR and CCPA standards, thanks to our membership in the Ethical Web Data Collection Initiative.

Pricing Options:

Standard Datasets: choose from various ready-to-use datasets with standardized data schemas, priced from $1,000/month.

Custom Datasets: Tailor datasets from any public web domain to your unique business needs. Contact our sales team for custom pricing.

Experience a seamless journey with Oxylabs:

• Understanding your data needs: We work closely to understand your business nature and daily operations, defining your unique data requirements.
• Developing a customized solution: Our experts create a custom framework to extract public data using our in-house web scraping infrastructure.
• Delivering data sample: We provide a sample for your feedback on data quality and the entire delivery process.
• Continuous data delivery: We continuously collect public data and deliver custom datasets per the agreed frequency.

Unlock the power of data with Oxylabs' Company Datasets and supercharge your business insights today!

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.

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.

United States Non Farm Payroll Nowcast: sa: MoM: Contribution: Business Statistics: Business Application data was reported at 2.125 % in 03 Mar 2025. This records an increase from the previous number of 1.848 % for 24 Feb 2025. United States Non Farm Payroll Nowcast: sa: MoM: Contribution: Business Statistics: Business Application data is updated weekly, averaging 0.690 % from Jan 2020 (Median) to 03 Mar 2025, with 267 observations. The data reached an all-time high of 4.210 % in 17 Feb 2020 and a record low of 0.004 % in 01 Jun 2020. United States Non Farm Payroll Nowcast: sa: MoM: Contribution: Business Statistics: Business Application data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s United States – Table US.CEIC.NC: CEIC Nowcast: Employment: Non Farm Payroll.

Abstract copyright UK Data Service and data collection copyright owner.

The Business Structure Database (BSD) contains a small number of variables for almost all business organisations in the UK. The BSD is derived primarily from the Inter-Departmental Business Register (IDBR), which is a live register of data collected by HM Revenue and Customs via VAT and Pay As You Earn (PAYE) records. The IDBR data are complimented with data from ONS business surveys. If a business is liable for VAT (turnover exceeds the VAT threshold) and/or has at least one member of staff registered for the PAYE tax collection system, then the business will appear on the IDBR (and hence in the BSD). In 2004 it was estimated that the businesses listed on the IDBR accounted for almost 99 per cent of economic activity in the UK. Only very small businesses, such as the self-employed were not found on the IDBR.

The IDBR is frequently updated, and contains confidential information that cannot be accessed by non-civil servants without special permission. However, the ONS Virtual Micro-data Laboratory (VML) created and developed the BSD, which is a 'snapshot' in time of the IDBR, in order to provide a version of the IDBR for research use, taking full account of changes in ownership and restructuring of businesses. The 'snapshot' is taken around April, and the captured point-in-time data are supplied to the VML by the following September. The reporting period is generally the financial year. For example, the 2000 BSD file is produced in September 2000, using data captured from the IDBR in April 2000. The data will reflect the financial year of April 1999 to March 2000. However, the ONS may, during this time, update the IDBR with data on companies from its own business surveys, such as the Annual Business Survey (SN 7451).

The Business Structure Database Longitudinal, 1997-2013 was compiled by Michael Anyadike-Danes, Aston Business School, with support from Economic and Social Research Council funding.

Researchers are advised to read the documentation accompanying the main BSD collection held by the UK Data Archive under SN 6697 before applying for or using the longitudinal data.

Linking to other business studies
These data contain IDBR reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

For the second edition (April 2019), the full postcodes have been replaced with only the first part of the postcode (e.g., SW1V rather than SW1V 2QQ) in the two geography data files. A look up file that includes postcode districts has been added so that users can still aggregate to higher geographies.

• enterprise birth and death date file
• enterprise employees file, giving the total number of employees (excluding owners) of each enterprise
• two geography files, including Government Office Regions and postcodes, both at birth and throughout 1997-2013
• two Standard Industrial Classification code files both at birth and throughout 1997-2013

Survey of advanced technology, use of business practices, by business practice type, North American Industry Classification System (NAICS) and enterprise size for Canada and certain provinces, in 2014.

Core Business Statistics Series, 2012: Franchise Status for Selected Industries and States

Graph and download economic data for Business Applications: Total for All NAICS in Florida (BABATOTALNSAFL) from Jul 2004 to Feb 2025 about business applications, business, FL, and USA.

To create the dataset, the top 10 countries leading in the incidence of COVID-19 in the world were selected as of October 22, 2020 (on the eve of the second full of pandemics), which are presented in the Global 500 ranking for 2020: USA, India, Brazil, Russia, Spain, France and Mexico. For each of these countries, no more than 10 of the largest transnational corporations included in the Global 500 rating for 2020 and 2019 were selected separately. The arithmetic averages were calculated and the change (increase) in indicators such as profitability and profitability of enterprises, their ranking position (competitiveness), asset value and number of employees. The arithmetic mean values of these indicators for all countries of the sample were found, characterizing the situation in international entrepreneurship as a whole in the context of the COVID-19 crisis in 2020 on the eve of the second wave of the pandemic. The data is collected in a general Microsoft Excel table. Dataset is a unique database that combines COVID-19 statistics and entrepreneurship statistics. The dataset is flexible data that can be supplemented with data from other countries and newer statistics on the COVID-19 pandemic. Due to the fact that the data in the dataset are not ready-made numbers, but formulas, when adding and / or changing the values in the original table at the beginning of the dataset, most of the subsequent tables will be automatically recalculated and the graphs will be updated. This allows the dataset to be used not just as an array of data, but as an analytical tool for automating scientific research on the impact of the COVID-19 pandemic and crisis on international entrepreneurship. The dataset includes not only tabular data, but also charts that provide data visualization. The dataset contains not only actual, but also forecast data on morbidity and mortality from COVID-19 for the period of the second wave of the pandemic in 2020. The forecasts are presented in the form of a normal distribution of predicted values and the probability of their occurrence in practice. This allows for a broad scenario analysis of the impact of the COVID-19 pandemic and crisis on international entrepreneurship, substituting various predicted morbidity and mortality rates in risk assessment tables and obtaining automatically calculated consequences (changes) on the characteristics of international entrepreneurship. It is also possible to substitute the actual values identified in the process and following the results of the second wave of the pandemic to check the reliability of pre-made forecasts and conduct a plan-fact analysis. The dataset contains not only the numerical values of the initial and predicted values of the set of studied indicators, but also their qualitative interpretation, reflecting the presence and level of risks of a pandemic and COVID-19 crisis for international entrepreneurship.

A November 2021 survey of online users in the United States found that 81 percent of respondents had used Google as a tool to evaluate local businesses in the past 12 months. Yelp was ranked second with over half of respondents using the review platform for such purpose.

Business Analytics Market was valued at USD 84.42 Billion in 2024 and is projected to reach USD 176.14 Billion by 2031, growing at a CAGR of 9.63% from 2024 to 2031.

Global Business Analytics Market Drivers

The market drivers for the Business Analytics Market can be influenced by various factors. These may include:

Growing Adoption of Big Data Analytics: In order to extract meaningful insights from their data, organizations are progressively using big data analytics in response to the exponential expansion of data. Making educated decisions through data analysis is facilitated by business analytics.
Growing Need for Data-driven Decision Making: In order to obtain a competitive edge, businesses are realizing the significance of data-driven decision making. The methods and instruments for data analysis and significant insights extraction for improved decision-making are offered by business analytics.
Growing Need for Predictive and Prescriptive Analytics: Predictive and prescriptive analytics are becoming more and more in demand as a means of projecting future trends and results. Businesses can use business analytics to prescribe activities to achieve desired outcomes and forecast future outcomes based on previous data.
Growing Emphasis on Customer Analytics: As e-commerce and digital marketing gain traction, companies are putting more of an emphasis on comprehending the behavior and preferences of their customers. In order to increase consumer engagement and personalize marketing efforts, business analytics is used to analyze customer data.
Emergence of Advanced Technologies: The use of advanced analytics solutions is being propelled by developments in fields like artificial intelligence (AI), machine learning (ML), and natural language processing (NLP). Businesses may now analyze data more effectively and gain deeper insights thanks to these technologies.
Operational Efficiency and Cost Optimization Are Necessary: Companies are always under pressure to increase operational efficiency and reduce costs. Business analytics promotes market expansion by assisting in the identification of opportunities for process and cost-cutting enhancements.
Compliance and Regulatory Requirements: The use of business analytics solutions for risk management and compliance reporting is being fueled by the growing regulatory requirements in a number of industries, including healthcare, banking, and retail.

InfoGroup’s Historical Business Backfile consists of geo-coded records of millions of US businesses and other organizations that contain basic information on each entity, such as: contact information, industry description, annual revenues, number of employees, year established, and other data. Each annual file consists of a “snapshot” of InfoGroup’s data as of the last day of each year, creating a time series of data 1997-2019. Access is restricted to current Harvard University community members. Use of Infogroup US Historical Business Data is subject to the terms and conditions of a license agreement (effective March 16, 2016) between Harvard and Infogroup Inc. and subject to applicable laws. Most data files are available in either .csv or .sas format. All data files are compressed into an archive in .gz, or GZIP, format. Extraction software such as 7-Zip is required to unzip these archives.

Data on businesses collected by statistical agencies are challenging to protect.Many businesses have unique characteristics, and distributions of employment,sales, and profits are highly skewed. Attackers wishing to conduct identificationattacks often have access to much more information than for any individual. Asa consequence, most disclosure avoidance mechanisms fail to strike an accept-able balance between usefulness and confidentiality protection. Detailed aggregatestatistics by geography or detailed industry classes are rare, public-use microdataon businesses are virtually inexistant, and access to confidential microdata can beburdensome. Synthetic microdata have been proposed as a secure mechanism topublish microdata, as part of a broader discussion of how to provide broader accessto such datasets to researchers. In this article, we document an experiment to cre-ate analytically valid synthetic data, using the exact same model and methods previ-ously employed for the United States, for data from two different countries: Canada(Longitudinal Employment Analysis Program (LEAP)) and Germany (EstablishmentHistory Panel (BHP)). We assess utility and protection, and provide an assessmentof the feasibility of extending such an approach in a cost-effective way to other data.

South Dakota high-propensity business applications was at level of 80 on the week of January 25, unchanged from the previous week. High‐Propensity Business Applications (HBA): Business Applications (BA) that have a high propensity of turning into businesses with payroll. The identification of high‐propensity applications is based on the characteristics of applications revealed on the IRS Form SS‐4 that are associated with a high rate of business formation. High‐propensity applications include applications: (a) for a corporate entity, (b) that indicate they are hiring employees, purchasing a business or changing organizational type, (c) that provide a first wages‐paid date (planned wages); or (d) that have a NAICS industry code in manufacturing (31‐33), retail stores (44), health care (62), or restaurants/food service (72).

Graph and download economic data for Business Applications for the United States (BUSAPPWNSAUS) from 2006-01-07 to 2025-03-01 about business applications, business, and USA.

This dataset provides comprehensive local business and point of interest (POI) data from Google Maps in real-time. It includes detailed business information such as addresses, websites, phone numbers, emails, ratings, reviews, business hours, and over 40 additional data points. Perfect for applications requiring local business data (b2b lead generation, b2b marketing), store locators, and business directories. The dataset is delivered in a JSON format via REST API.

This statistic shows the business use of biometric authentication in North America and Europe as of 2018. Smartphone is the most commonly used platform for biometric authentication in the workplace - 46 percent of the respondents said that their company currently used smartphones for this purpose.

Underlying data from the publication 'Research to understand the barriers to take up and use of business support' [URN 11/1288]. Data from a survey of 1,202 employer SMEs in England undertaken in March 2011. The survey was designed to provide statistically robust evidence of business use and non use of external business support services, differentiating between private sector and public sector sources of both routine information and strategic advice. The survey aimed to produce a broadly representative sample of SME employers and used a random stratified sample from the Experian database adopting quotas in order to capture sufficient numbers of businesses across key categories (age, size, sector, region). The data presented in the published report was weighted by size band to correct for over-sampling amongst larger SMEs.