The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching 149 zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than 394 zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just two percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of 19.2 percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached 6.7 zettabytes.

The average daily in-home data usage in the United States has increased significantly during the coronavirus (COVID-19) outbreak in March 2020. Compared to the same time in March 2019 the daily average in-home data usage has increased by 38 percent to 16.6 gigabytes, up from 12 gigabytes in March 2019. The increase can be observed across almost all device categories with the data usage of gaming consoles and smartphones increasing the most.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

Annual fact sheets providing statistics on the Social Security and Supplemental Security Income programs, including the number of people receiving benefits and the amount of total monthly payments in each state, territory, and Congressional district. Report for 2020.

The value of data market in the United States was estimated to exceed 211 billion euros in 2020, an increase from the previous year. The U.S. data market has been growing over the measured period.

This annual report provides program and demographic information on the people who receive Social Security Disability Insurance Program benefits. This edition presents a series of detailed tables on the three categories of beneficiaries: disabled workers, disabled widowers, and disabled adult children. Numbers presented in these tables may differ slightly from other published statistics because all tables, except those using data from the Survey of Income and Program Participation, are based on 100 percent data files. Report for 2020.

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since the first reported coronavirus case in Washington State on Jan. 21, 2020, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

The 2020 SPAM (Spatial Production Allocation Model) products, encompassing crop area, yield, and production at a 5-minute grid resolution, have been developed by Zhe Guo, Shuang Zhou, and Liangzhi You. Employing a diverse range of inputs, IFPRI's Spatial Production Allocation Model (SPAM) utilizes a cross-entropy method to generate plausible estimations of crop distribution within disaggregated units. By transitioning data from broader units like countries and sub-national provinces to more granular units such as grid cells, SPAM unveils spatial patterns of crop performance, forming a global grid-scape where geography intersects with agricultural production systems. Enhancing spatial comprehension of crop production systems empowers policymakers and donors to effectively target agricultural and rural development policies and investments, thereby enhancing food security and fostering growth while minimizing environmental impacts.

In 2020, 79 percent of UN Member States had a national open government data (OGD) portal, up from 47 percent in 2018. In addition, 59 percent of countries had a national OGD policy as of the last recorded period.

This statistical release presents experimental statistics on government grants spending for the financial year 2019 to 2020. The scope of this release is covered in the Government Grants Statistics 2019 to 2020.

Government Grants Management Function (GGMF) works closely with government departments to understand and resolve data quality issues; with this dataset being the most complete view of government grant spending published to date. In the https://draft-origin.publishing.service.gov.uk/government/statistics/government-grants-statistics-2019-20/2019-20-government-grants-statistics" class="govuk-link">Government grants statistics 2019 to 2020 we provide a number of notes and caveats that will help inform the interpretation of this data.

We continually seek to improve these annual publications and we encourage you to fill out our https://docs.google.com/forms/d/e/1FAIpQLSeLFZ1fQtS_LYlQ_UZPG3xtYnSPbtZvvMkK-VAqc5apn8cyFQ/viewform" class="govuk-link">feedback form if you use these statistics.

The Law Enforcement Management and Administrative Statistics (LEMAS) survey collects data from a nationally representative sample of general-purpose agencies (i.e., local and county police departments, sheriffs' offices, and primary state police agencies). The 2020 LEMAS sample design called for the survey questionnaire to be sent to 3,499 general purpose law enforcement agencies, including 2,631 local and county police departments, 819 sheriffs' offices, and the 49 primary state police departments (Hawaii does not have a primary state police agency). The design called for all agencies employing 100 or more full-time equivalent sworn personnel to be included with certainty (self-representing), and for smaller agencies to be sampled from strata based on number of full-time equivalent sworn officers and type of agency. A total of 37 local police departments were determined to be out-of-scope for the survey because they had closed, had less than one full-time equivalent sworn officer, had contracted out their services with another law enforcement agency, or only had special enforcement responsibilities. The final mail out total of 3,462 agencies included 2,611 local police departments, 802 sheriffs' offices, and the 49 state agencies.

This dataset collection encompasses a group of interrelated tables sourced from the Statistics Centre (Tilastokeskus) in Finland. The tables contain a wealth of information pulled from the Statistics Centre's service interface (WFS). The data is meticulously organized into columns and rows within the tables, each one presenting a comprehensive view of specific statistical areas. The data within this collection provides a detailed insight into various statistical areas, making it an invaluable resource for anyone seeking thorough knowledge in this domain. This dataset is licensed under CC BY 4.0 (Creative Commons Attribution 4.0, https://creativecommons.org/licenses/by/4.0/deed.fi).

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.

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: 2020NES Table: NS2000NESData downloaded from: Census Bureau's API for Nonemployer StatisticsDate of API call: December 12, 2023National 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.

From 2020 to 2022, the total enterprise data volume will go from approximately one petabyte (PB) to 2.02 petabytes. This is a 42.2 percent average annual growth over these two years. It is worth noting that internally managed data centers will continue to be the locations in which most of the data will be stored.