The Free Brazilian Repository for Open Soil Data – febr, www.ufsm.br/febr – is a centralized repository targeted at storing open soil data and serving it in a standardized and harmonized format. The repository infrastructure was built using open source and/or free (of cost) software, and was primarily designed for the individual management of datasets. A dataset-driven structure helps datasets authors to be properly acknowledged. Moreover, it gives the flexibility to accommodate many types of data of any soil variable. This is accomplished by storing each dataset using a collection of spreadsheets accessible through an online application. Spreadsheets are familiar to any soil scientist, the reason why it is easier to enter, manipulate and visualize soil data in febr. They also facilitate the participation of soil survey experts in the recovery and quality assessment of legacy data. Soil scientists can help in the definition of standards and data management choices through a public discussion forum, febr-forum@googlegroups.com. A comprehensive documentation is available to guide febr maintainers and data contributors. A detailed catalog gives access to the 14 477 soil observations – 42% of them from south and southeastern Brazil – from 232 datasets contained in febr. Global and dataset-specific visualization and search tools and multiple download facilities are available. The latter includes standard file formats and connections with R and QGIS through the febr package. Various products can be derived from data in febr: specialized databases, pedotransfer functions, fertilizer recommendation guides, classification systems, and detailed soil maps. By sharing data through a centralized soil data storing and sharing facility, soil scientists from different fields have the opportunity to increase collaboration and the much needed soil knowledge.

Brazil Lending Rate: per Annum: Pre-Fixed: Individuals: Leasing of Vehicles: Banco Luso Brasileiro S.A. data was reported at 0.000 % pa in 03 Jul 2019. This stayed constant from the previous number of 0.000 % pa for 02 Jul 2019. Brazil Lending Rate: per Annum: Pre-Fixed: Individuals: Leasing of Vehicles: Banco Luso Brasileiro S.A. data is updated daily, averaging 0.000 % pa from Jan 2012 (Median) to 03 Jul 2019, with 1641 observations. The data reached an all-time high of 49.120 % pa in 12 Dec 2012 and a record low of 0.000 % pa in 03 Jul 2019. Brazil Lending Rate: per Annum: Pre-Fixed: Individuals: Leasing of Vehicles: Banco Luso Brasileiro S.A. data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Interest and Foreign Exchange Rates – Table BR.MB029: Lending Rate: per Annum: by Banks: Pre-Fixed: Individuals: Leasing of Vehicles. Lending Rate: Daily: Interest rates disclosed represent the total cost of the transaction to the client, also including taxes and operating. These rates correspond to the average fees in the period indicated in the tables. There are presented only institutions that had granted during the period determined. In general, institutions practicing different rates within the same type of credit. Thus, the rate charged to a customer may differ from the average. Several factors such as the time and volume of the transaction, as well as the guarantees offered, explain the differences between interest rates. Certain institutions grant allowance of the use of the term overdraft. However, this is not considered in the calculation of rates of this type. It should be noted that the overdraft is a modality that has high interest rates. Thus, its use should be restricted to short periods. If the customer needs resources for a longer period, should find ways to offer lower rates. The Brazilian Central Bank publishes these data with a delay about 20 days with relation to the reference period, thus allowing sufficient time for all Financial Institutions to deliver the relevant information. Interest rates presented in this set of tables correspond to averages weighted by the values of transactions conducted in the five working days specified in each table. These rates represent the average effective cost of loans to customers, consisting of the interest rates actually charged by financial institutions in their lending operations, increased tax burdens and operational incidents on the operations. The interest rates shown are the average of the rates charged in the various operations performed by financial institutions, in each modality. In one discipline, interest rates may differ between customers of the same financial institution. Interest rates vary according to several factors, such as the value and quality of collateral provided in the operation, the proportion of down payment operation, the history and the registration status of each client, the term of the transaction, among others . Institutions with “zero” did not operate on modalities for those periods or did not provide information to the Central Bank of Brazil. The Central Bank of Brazil assumes no responsibility for delay, error or other deficiency of information provided for purposes of calculating average rates presented in this

The Brazil Data Center Server Market is Segmented by Form Factor (Blade Server, Rack Server, and Tower Server), and by End User (IT and Telecommunication, BFSI, Government, Media and Entertainment, and Other End Users). The Market Sizes and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.

The USDBRL increased 0.0293 or 0.51% to 5.7285 on Wednesday March 26 from 5.6992 in the previous trading session. Brazilian Real - values, historical data, forecasts and news - updated on March of 2025.

The Brazilian Zooarch Database (ZooarchBR) is the first collaborative and open access zooarchaeological database in Brazil, where the user can not only view the available data, but also contribute by entering new/additional information to expand the faunal data recorded in Brazilian archaeological sites. The data will also be integrated into the Sistema de Informação sobre a Biodiversidade Brasileira (SiBBr) and Global Biodiversity Information Facility (GBIF). Reference (version 1): Fossile, T., Ferreira, J, Colonese, A.C. 2023. Brazilian Zooarch Database (ZooarchBR): a database of the archaeological fauna of Brazil, Revista de Arqueologia da Sociedade de Arqueologia Brasileira (ISSN 0102-0420 - Press Version; ISSN 1982-1999 - Online Version), v. 36 n. 3 (2023): Special issue Zooarqueologia Neotropical, Editors C. Borges; P. Fernandéz; A. S. Muñoz; R. C. C. L. Souza, Neotropical Zooarchaeology Working Group of International Council for Archaeozoology (NZWG-ICAZ). DOI https://doi.org/10.24885/sab.v36i3.1088. (Português) O Brazilian Zooarch Database (ZooarchBR) é o primeiro banco de dados zooarqueológico colaborativo e de acesso aberto do Brasil onde o usuário pode visualizar os dados disponíveis e contribuir na inserção de novos dados para expansão da fauna registrada em sítios arqueológicos no país. Os dados também serão integrados ao Sistema de Informação sobre a Biodiversidade Brasileira (SiBBr) e ao Global Biodiversity Information Facility (GBIF). Referência (versão 1): Fossile, T., Ferreira, J., Colonese, A.C. 2023. Brazilian Zooarch Database (ZooarchBR): banco de dados da fauna arqueológica do Brasil, Revista de Arqueologia da Sociedade de Arqueologia Brasileira (ISSN 0102-0420 - Versão Impressa; ISSN 1982-1999 - Versão Online), v. 36 n. 3 (2023): Dossiê Zooarqueologia Neotropical, Editores C. Borges; P. Fernandéz; A. S. Muñoz; R. C. C. L. Souza, Neotropical Zooarchaeology Working Group of International Council for Archaeozoology (NZWG-ICAZ). DOI https://doi.org/10.24885/sab.v36i3.1088. This work was funded by the ERC Consolidator project TRADITION, which has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 817911. This work contributes to the "ICTA-UAB María de Maeztu" Programme for Units of Excellence of the Spanish Ministry of Science and Innovation (CEX2019-000940-M). This work was also funded by EarlyFoods (Evolution and impact of early food production systems), 2021 SGR 00527.

The Brazil Data Center Storage Market Report is Segmented by Storage Technology (Network Attached Storage (NAS), Storage Area Network (SAN), and Direct Attached Storage (DAS)), Storage Type (Traditional Storage, All-Flash Storage, Hybrid Storage), and End User (IT & Telecommunication, BFSI, Government, Media & Entertainment, and Other End-User). The Market Sizes and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

National coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for Brazil is 1002.

Mode of data collection

Landline and mobile telephone

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

Poland Exports to Brazil was US$949.26 Million during 2024, according to the United Nations COMTRADE database on international trade. Poland Exports to Brazil - data, historical chart and statistics - was last updated on March of 2025.

The Brazil Data Center Market is segmented by Hotspot (Rio de Janeiro, Sao Paulo), by Data Center Size (Large, Massive, Medium, Mega, Small), by Tier Type (Tier 1 and 2, Tier 3, Tier 4) and by Absorption (Non-Utilized, Utilized). Market Volume in Megawatt (MW) is presented. Key Data Points observed include IT load capacity for existing and upcoming data centers, current and upcoming hotspots, average mobile data consumption, volume of fiber cable connectivity in KM, existing and upcoming submarine cables, rack space utilization, and number of data centers by tier.

When asked about "Most common mobile data plans", 26 percent of Brazilian respondents answer "3-5 GB". This online survey was conducted in 2024, among 1,930 consumers.

The revenue in the data center market in Brazil was forecast to continuously increase between 2024 and 2029 by in total 1.7 billion U.S. dollars (+31.95 percent). After the ninth consecutive increasing year, the indicator is estimated to reach 7.06 billion U.S. dollars and therefore a new peak in 2029. Find more key insights for the revenue in countries like Suriname, Nicaragua, and Costa Rica.. The Statista Market Insights cover a broad range of additional markets.

UNICEF's country profile for Brazil, including under-five mortality rates, child health, education and sanitation data.

Chile Imports from Brazil was US$8.77 Billion during 2023, according to the United Nations COMTRADE database on international trade. Chile Imports from Brazil - data, historical chart and statistics - was last updated on March of 2025.

Lithuania Imports from Brazil was US$39.07 Million during 2023, according to the United Nations COMTRADE database on international trade. Lithuania Imports from Brazil - data, historical chart and statistics - was last updated on February of 2025.

Brazil Imports from Vietnam was US$3.87 Billion during 2024, according to the United Nations COMTRADE database on international trade. Brazil Imports from Vietnam - data, historical chart and statistics - was last updated on March of 2025.

Os dados de PIB nominal do Brasil foram registrados em 486.1 USD bn em 2023-03. Este registro de uma queda com relação aos números anteriores de 490.6 USD bn em 2022-12. Os dados de PIB nominal do Brasil são atualizados trimestral, com uma média de 284.6 USD bn em 1990-03 até 2023-03, com 133 observações. Os dados alcançaram um alto recorde de 680.4 USD bn em 2011-06 e um baixo recorde de 89.3 USD bn em 1991-03. Os dados de PIB nominal do Brasil permanecem com status ativo na CEIC e são reportados pela fonte: CEIC Data. Os dados são classificados sob o World Trend Plus’ Global Economic Monitor – Table: Nominal GDP: USD: Quarterly.

The Brazil Data Center Construction Market Report is Segmented by Infrastructure (Electrical Infrastructure [Power Distribution Solutions (PDUs, Transfer Switches, Switchgear, Power Panels and Components, and Other Power Distribution Solutions), Power Backup Solutions (UPS and Generators), and Services (Design and Consulting, Integration, and Support and Maintenance)], Mechanical Infrastructure [Cooling Systems (Immersion Cooling, Direct-To-Chip Cooling, Rear Door Heat Exchanger, and In-Row and In-Rack Cooling), Racks, and Other Mechanical Infrastructures], and General Construction), Tier Type (Tier 1 and 2, Tier 3, and Tier 4), and End User (Banking, Financial Services, and Insurance, IT and Telecommunications, Government and Defense, Healthcare, and Other End Users). The Market Sizes and Forecasts are Provided in Terms of Value (USD) for the Above Segments.

Graph and download economic data for Real Broad Effective Exchange Rate for Brazil (RBBRBIS) from Jan 1994 to Feb 2025 about Brazil, broad, exchange rate, currency, real, and rate.

Brazil Loans: Economic Activity: Demand: Exports of Goods and Services data was reported at 300.668 1995=100 in Mar 2018. This records an increase from the previous number of 287.233 1995=100 for Feb 2018. Brazil Loans: Economic Activity: Demand: Exports of Goods and Services data is updated monthly, averaging 202.642 1995=100 from Jan 1991 (Median) to Mar 2018, with 327 observations. The data reached an all-time high of 342.494 1995=100 in Jun 2015 and a record low of 62.450 1995=100 in Sep 1991. Brazil Loans: Economic Activity: Demand: Exports of Goods and Services data remains active status in CEIC and is reported by Serasa Experian. The data is categorized under Brazil Premium Database’s Monetary – Table BR.KAB032: Loans: Economic Activity. Constructed by making use of established statistical techniques for temporal disaggregation, aims to provide a set of statistics on monthly basis to reflect on this time scale, the evolution of the main variable that synthesizes the evolution of the Brazilian economy: Gross Domestic Product (GDP) computed under the Quarterly National Accounts System, published by IBGE (Brazilian Institute of Economics and Statistics). The indicators presented in this table specifically cover all the Brazilian territory and its results are divided into three major groups: GDP, Supply and Demand. GDP: Based on the Market Prices indicator Supply: Composed of the most significant supply indicators: Taxes on Products, Agricultural, Industry and Services Demand: It is composed by the most significant demand indicators: Household Consumption, Government Consumption, Gross Fixed Capital Formation, Exports of Goods and Services and Imports of Goods and Services. Construído através da utilização de técnicas estatísticas consagradas de desagregação temporal, o Indicador Serasa Experian de Atividade Econômica (PIB Mensal) tem por objetivo fornecer um conjunto de estatísticas de alta freqüência, isto é, de periodicidade mensal, que reflitam, nesta escala de tempo, a evolução da principal variável que sintetiza a evolução da economia brasileira: o Produto Interno Bruto (PIB) computado no âmbito do Sistema de Contas Nacionais Trimestrais, divulgado pelo IBGE. Os indicadores apresentados nesta tabela cobrir especificamente todo o território brasileiro e seus resultados são divididos em três grandes grupos: o PIB, Oferta e Demanda. PIB: Com base no indicador de Preços de Mercado Oferta: Composto pelos indicadores de oferta mais significativas: Impostos sobre Produtos, Agropecuária, Indústria e Serviços Demanda: É composto pelos indicadores de demanda mais significativas: consumo das famílias, o Consumo do Governo, a Formação Bruta de Capital Fixo, as Exportações de Bens e Serviços e Importações de Bens e Serviços.

Brazil Lending Rate: per Annum: Pre-Fixed: Individuals: Mortgages with Regulated Rates: Banco Sumitomo Mitsui Brasileiro S.A. data was reported at 0.000 % pa in 03 Jul 2019. This stayed constant from the previous number of 0.000 % pa for 02 Jul 2019. Brazil Lending Rate: per Annum: Pre-Fixed: Individuals: Mortgages with Regulated Rates: Banco Sumitomo Mitsui Brasileiro S.A. data is updated daily, averaging 0.000 % pa from Jan 2012 (Median) to 03 Jul 2019, with 1867 observations. The data reached an all-time high of 0.000 % pa in 03 Jul 2019 and a record low of 0.000 % pa in 03 Jul 2019. Brazil Lending Rate: per Annum: Pre-Fixed: Individuals: Mortgages with Regulated Rates: Banco Sumitomo Mitsui Brasileiro S.A. data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Interest and Foreign Exchange Rates – Table BR.MB037: Lending Rate: per Annum: by Banks: Pre-Fixed: Individuals: Mortgages with Regulated Rates. Lending Rate: Daily: Interest rates disclosed represent the total cost of the transaction to the client, also including taxes and operating. These rates correspond to the average fees in the period indicated in the tables. There are presented only institutions that had granted during the period determined. In general, institutions practicing different rates within the same type of credit. Thus, the rate charged to a customer may differ from the average. Several factors such as the time and volume of the transaction, as well as the guarantees offered, explain the differences between interest rates. Certain institutions grant allowance of the use of the term overdraft. However, this is not considered in the calculation of rates of this type. It should be noted that the overdraft is a modality that has high interest rates. Thus, its use should be restricted to short periods. If the customer needs resources for a longer period, should find ways to offer lower rates. The Brazilian Central Bank publishes these data with a delay about 20 days with relation to the reference period, thus allowing sufficient time for all Financial Institutions to deliver the relevant information. Interest rates presented in this set of tables correspond to averages weighted by the values of transactions conducted in the five working days specified in each table. These rates represent the average effective cost of loans to customers, consisting of the interest rates actually charged by financial institutions in their lending operations, increased tax burdens and operational incidents on the operations. The interest rates shown are the average of the rates charged in the various operations performed by financial institutions, in each modality. In one discipline, interest rates may differ between customers of the same financial institution. Interest rates vary according to several factors, such as the value and quality of collateral provided in the operation, the proportion of down payment operation, the history and the registration status of each client, the term of the transaction, among others . Institutions with “zero” did not operate on modalities for those periods or did not provide information to the Central Bank of Brazil. The Central Bank of Brazil assumes no responsibility for delay, error or other deficiency of information provided for purposes of calculating average rates presented in this