The International Google Trends dataset will provide critical signals that individual users and businesses alike can leverage to make better data-driven decisions. This dataset simplifies the manual interaction with the existing Google Trends UI by automating and exposing anonymized, aggregated, and indexed search data in BigQuery. This dataset includes the Top 25 stories and Top 25 Rising queries from Google Trends. It will be made available as two separate BigQuery tables, with a set of new top terms appended daily. Each set of Top 25 and Top 25 rising expires after 30 days, and will be accompanied by a rolling five-year window of historical data for each country and region across the globe, where data is available. The International Google Trends dataset will provide critical signals that individual users and businesses alike can leverage to make better data-driven decisions. This dataset simplifies the manual interaction with the existing Google Trends UI by automating and exposing anonymized, aggregated, and indexed search data in BigQuery. This dataset includes the Top 25 stories and Top 25 Rising queries from Google Trends. It will be made available as two separate BigQuery tables, with a set of new top terms appended daily. Each set of Top 25 and Top 25 rising expires after 30 days, and will be accompanied by a rolling five-year window of historical data for each country and region across the globe, where data is available. This Google dataset is hosted in Google BigQuery as part of Google Cloud's Datasets solution and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery

The dataset provides 12 months (August 2016 to August 2017) of obfuscated Google Analytics 360 data from the Google Merchandise Store , a real ecommerce store that sells Google-branded merchandise, in BigQuery. It’s a great way analyze business data and learn the benefits of using BigQuery to analyze Analytics 360 data Learn more about the data The data includes The data is typical of what an ecommerce website would see and includes the following information:Traffic source data: information about where website visitors originate, including data about organic traffic, paid search traffic, and display trafficContent data: information about the behavior of users on the site, such as URLs of pages that visitors look at, how they interact with content, etc. Transactional data: information about the transactions on the Google Merchandise Store website.Limitations: All users have view access to the dataset. This means you can query the dataset and generate reports but you cannot complete administrative tasks. Data for some fields is obfuscated such as fullVisitorId, or removed such as clientId, adWordsClickInfo and geoNetwork. “Not available in demo dataset” will be returned for STRING values and “null” will be returned for INTEGER values when querying the fields containing no data.This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery

The Google Trends dataset will provide critical signals that individual users and businesses alike can leverage to make better data-driven decisions. This dataset simplifies the manual interaction with the existing Google Trends UI by automating and exposing anonymized, aggregated, and indexed search data in BigQuery. This dataset includes the Top 25 stories and Top 25 Rising queries from Google Trends. It will be made available as two separate BigQuery tables, with a set of new top terms appended daily. Each set of Top 25 and Top 25 rising expires after 30 days, and will be accompanied by a rolling five-year window of historical data in 210 distinct locations in the United States. This Google dataset is hosted in Google BigQuery as part of Google Cloud's Datasets solution and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery

Google Patents Research Data contains the output of much of the data analysis work used in Google Patents (patents.google.com), including machine translations of titles and abstracts from Google Translate, embedding vectors, extracted top terms, similar documents, and forward references.

This table contains release notes for the majority of generally available Google Cloud products found on cloud.google.com . You can use this BigQuery public dataset to consume release notes programmatically across all products. HTML versions of release notes are available within each product's documentation and also in a filterable format at https://console.cloud.google.com/release-notes . This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

This dataset from Dimensions.ai contains all published articles, preprints, clinical trials, grants and research datasets that are related to COVID-19. This growing collection of research information now amounts to hundreds of thousands of items, and it is the only dataset of its kind. You can find an overview of the content in this interactive Data Studio dashboard: https://reports.dimensions.ai/covid-19/ The full metadata includes the researchers and organizations involved in the research, as well as abstracts, open access status, research categories and much more. You may wish to use the Dimensions web application to explore the dataset: https://covid-19.dimensions.ai/. This dataset is for researchers, universities, pharmaceutical & biotech companies, politicians, clinicians, journalists, and anyone else who wishes to explore the impact of the current COVID-19 pandemic. It is updated daily, and free for anyone to access. Please share this information with anyone you think would benefit from it. If you have any suggestions as to how we can improve our search terms to maximise the volume of research related to COVID-19, please contact us at support@dimensions.ai. About Dimensions: Dimensions is the largest database of research insight in the world. It contains a comprehensive collection of linked data related to the global research and innovation ecosystem, all in a single platform. This includes hundreds of millions of publications, preprints, grants, patents, clinical trials, datasets, researchers and organizations. Because Dimensions maps the entire research lifecycle, you can follow academic and industry research from early stage funding, through to output and on to social and economic impact. This Covid-19 dataset is a subset of the full database. The full Dimensions database is also available on BigQuery, via subscription. Please visit www.dimensions.ai/bigquery to gain access.Learn more

Stack Overflow is the largest online community for programmers to learn, share their knowledge, and advance their careers. Updated on a quarterly basis, this BigQuery dataset includes an archive of Stack Overflow content, including posts, votes, tags, and badges. This dataset is updated to mirror the Stack Overflow content on the Internet Archive, and is also available through the Stack Exchange Data Explorer. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

This repository contains the largest COVID-19 epidemiological database available in addition to a powerful set of expansive covariates. It includes open sourced data with a permissive license (enabling commercial use) relating to vaccinations, epidemiology, hospitalizations, demographics, economy, geography, health, mobility, government response, weather, and more. Moreover, the data merges daily time-series from hundreds of data sources at a fine spatial resolution, containing over 20,000 locations and using a consistent set of region keys. This dataset is available in both the US and EU regions of BigQuery at the following links: COVID-19 Open Data: US Region COVID-19 Open Data: EU Region All data in this dataset is retrieved automatically. When possible, data is retrieved directly from the relevant authorities, like a country's ministry of health. This dataset has significant public interest in light of the COVID-19 crisis. All bytes processed in queries against this dataset will be zeroed out, making this part of the query free. Data joined with the dataset will be billed at the normal rate to prevent abuse. After September 15, queries over these datasets will revert to the normal billing rate. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

The Quarterly Census of Employment and Wages (QCEW) program publishes a quarterly count of employment and wages reported by employers covering more than 95 percent of U.S. jobs, available at the county, MSA, state and national levels by industry. The dataset, hosted as part of the Cloud Public Datasets Program , gives county-level information on jobs and wages each quarter starting in 1990. The counties are identified by geoid which can easily be joined with both all FIPS codes or US county boundaries to unlock new insights within the data. Both of these datasets are available in BigQuery through the Cloud Public Datasets Cleaning and onboarding support for this dataset is provided by CARTO . This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

In an effort to help combat COVID-19, we created a COVID-19 Public Datasets program to make data more accessible to researchers, data scientists and analysts. The program will host a repository of public datasets that relate to the COVID-19 crisis and make them free to access and analyze. These include datasets from the New York Times, European Centre for Disease Prevention and Control, Google, Global Health Data from the World Bank, and OpenStreetMap. Free hosting and queries of COVID datasets As with all data in the Google Cloud Public Datasets Program , Google pays for storage of datasets in the program. BigQuery also provides free queries over certain COVID-related datasets to support the response to COVID-19. Queries on COVID datasets will not count against the BigQuery sandbox free tier , where you can query up to 1TB free each month. Limitations and duration Queries of COVID data are free. If, during your analysis, you join COVID datasets with non-COVID datasets, the bytes processed in the non-COVID datasets will be counted against the free tier, then charged accordingly, to prevent abuse. Queries of COVID datasets will remain free until Sept 15, 2021. The contents of these datasets are provided to the public strictly for educational and research purposes only. We are not onboarding or managing PHI or PII data as part of the COVID-19 Public Dataset Program. Google has practices & policies in place to ensure that data is handled in accordance with widely recognized patient privacy and data security policies. See the list of all datasets included in the program

This dataset contains current and historical demographic data on Google's workforce since the company began publishing diversity data in 2014. It includes data collected for government reporting and voluntary employee self-identification globally relating to hiring, retention, and representation categorized by race, gender, sexual orientation, gender identity, disability status, and military status. In some instances, the data is limited due to various government policies around the world and the desire to protect Googler confidentiality. All data in this dataset will be updated yearly upon publication of Google’s Diversity Annual Report . Google uses this data to inform its diversity, equity, and inclusion work. More information on our methodology can be found in the Diversity Annual Report. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

Dynamic World is a 10m near-real-time (NRT) Land Use/Land Cover (LULC) dataset that includes class probabilities and label information for nine classes. Dynamic World predictions are available for the Sentinel-2 L1C collection from 2015-06-27 to present. The revisit frequency of Sentinel-2 is between 2-5 days depending on latitude. Dynamic World predictions are generated for Sentinel-2 L1C images with CLOUDY_PIXEL_PERCENTAGE <= 35%. Predictions are masked to remove clouds and cloud shadows using a combination of S2 Cloud Probability, Cloud Displacement Index, and Directional Distance Transform. Images in the Dynamic World collection have names matching the individual Sentinel-2 L1C asset names from which they were derived, e.g: ee.Image('COPERNICUS/S2/20160711T084022_20160711T084751_T35PKT') has a matching Dynamic World image named: ee.Image('GOOGLE/DYNAMICWORLD/V1/20160711T084022_20160711T084751_T35PKT'). All probability bands except the "label" band collectively sum to 1. To learn more about the Dynamic World dataset and see examples for generating composites, calculating regional statistics, and working with the time series, see the Introduction to Dynamic World tutorial series. Given Dynamic World class estimations are derived from single images using a spatial context from a small moving window, top-1 "probabilities" for predicted land covers that are in-part defined by cover over time, like crops, can be comparatively low in the absence of obvious distinguishing features. High-return surfaces in arid climates, sand, sunglint, etc may also exhibit this phenomenon. To select only pixels that confidently belong to a Dynamic World class, it is recommended to mask Dynamic World outputs by thresholding the estimated "probability" of the top-1 prediction.

UPDATE: The Community Mobility Reports are no longer being updated as of October 15, 2022. All historical data will remain publicly available for research purposes. This dataset aims to provide insights into what has changed in response to policies aimed at combating COVID-19. It reports movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential. This dataset is intended to help remediate the impact of COVID-19. It shouldn’t be used for medical diagnostic, prognostic, or treatment purposes. It also isn’t intended to be used for guidance on personal travel plans. To learn more about the dataset, the place categories and how we calculate these trends and preserve privacy, visit our help center or read the data documentation All bytes processed in queries against this dataset will be zeroed out, making this part of the query free. Data joined with the dataset will be billed at the normal rate to prevent abuse. After September 15, queries over these datasets will revert to the normal billing rate. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

As global communities responded to COVID-19, we heard from public health officials that the same type of aggregated, anonymized insights we use in products such as Google Maps would be helpful as they made critical decisions to combat COVID-19. These Community Mobility Reports aimed to provide insights into what changed in response to policies aimed at combating COVID-19. The reports charted movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

This dataset contains two tables: creative_stats and removed_creative_stats. The creative_stats table contains information about advertisers that served ads in the European Economic Area or Turkey: their legal name, verification status, disclosed name, and location. It also includes ad specific information: impression ranges per region (including aggregate impressions for the European Economic Area), first shown and last shown dates, which criteria were used in audience selection, the format of the ad, and the ad topic. A link to the ad in the Google Ads Transparency Center is also provided. The removed_creative_stats table contains information about ads that served in the European Economic Area that Google removed: where and why they were removed and per-region information on when they served. The removed_creative_stats table also contains a link to the Google Ads Transparency Center for the removed ad. Data for both tables updates periodically and may be delayed from what appears on the Google Ads Transparency Center website. About BigQuery This data is hosted in Google BigQuery for users to easily query using SQL. Note that to use BigQuery, users must have a Google account and create a GCP project. This public dataset is included in BigQuery's 1TB/mo of free tier processing. Each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery . Download Dataset This public dataset is also hosted in Google Cloud Storage here and available free to use. Use this quick start guide to quickly learn how to access public datasets on Google Cloud Storage. We provide the raw data in JSON format, sharded across multiple files to support easier download of the large dataset. A README file which describes the data structure and our Terms of Service (also listed below) is included with the dataset. You can also download the results from a custom query. See here for options and instructions. Signed out users can download the full dataset by using the gCloud CLI. Follow the instructions here to download and install the gCloud CLI. To remove the login requirement, run "$ gcloud config set auth/disable_credentials True" To download the dataset, run "$ gcloud storage cp gs://ads-transparency-center/* . -R" This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

This large-scale open dataset consists of outlines of buildings derived from high-resolution 50 cm satellite imagery. It contains 1.8B building detections in Africa, Latin America, Caribbean, South Asia and Southeast Asia. The inference spanned an area of 58M km². For each building in this dataset we include the polygon describing its footprint on the ground, a confidence score indicating how sure we are that this is a building, and a Plus Code corresponding to the center of the building. There is no information about the type of building, its street address, or any details other than its geometry. Building footprints are useful for a range of important applications: from population estimation, urban planning and humanitarian response to environmental and climate science. The project is based in Ghana, with an initial focus on the continent of Africa and new updates on South Asia, South-East Asia, Latin America and the Caribbean. Inference was carried out during May 2023. For more details see the official website of the Open Buildings dataset.

In the U.S. public companies, certain insiders and broker-dealers are required to regularly file with the SEC. The SEC makes this data available online for anybody to view and use via their Electronic Data Gathering, Analysis, and Retrieval (EDGAR) database. The SEC updates this data every quarter going back to January, 2009. To aid analysis a quick summary view of the data has been created that is not available in the original dataset. The quick summary view pulls together signals into a single table that otherwise would have to be joined from multiple tables and enables a more streamlined user experience. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets.瞭解詳情

The FDIC's Institution Directory provides a list of all FDIC-insured institutions. The file includes demographic information related to the institution such as locational detail (name, city state, etc) and operating status (active, inactive, bank class, etc). The download file also contains key financial information reported by the FDIC-insured institution, such as total deposits, quarterly net income, and more. Additionally, the dataset includes data going back to 1996. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

The COVID-19 Search Trends symptoms dataset shows aggregated, anonymized trends in Google searches for a broad set of health symptoms, signs, and conditions. The dataset provides a daily or weekly time series for each region showing the relative volume of searches for each symptom. This dataset is intended to help researchers to better understand the impact of COVID-19. It shouldn't be used for medical diagnostic, prognostic, or treatment purposes. It also isn't intended to be used for guidance on personal travel plans. To learn more about the dataset, how we generate it and preserve privacy, read the data documentation . To visualize the data, try exploring these interactive charts and map of symptom search trends . As of Dec. 15, 2020, the dataset was expanded to include trends for Australia, Ireland, New Zealand, Singapore, and the United Kingdom. This expanded data is available in new tables that provide data at country and two subregional levels. We will not be updating existing state/county tables going forward. All bytes processed in queries against this dataset will be zeroed out, making this part of the query free. Data joined with the dataset will be billed at the normal rate to prevent abuse. After September 15, queries over these datasets will revert to the normal billing rate. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

Adapted from Wikipedia: OpenStreetMap (OSM) is a collaborative project to create a free editable map of the world. Created in 2004, it was inspired by the success of Wikipedia and more than two million registered users who can add data by manual survey, GPS devices, aerial photography, and other free sources. We've made available a number of tables (explained in detail below): history_* tables: full history of OSM objects planet_* tables: snapshot of current OSM objects as of Nov 2019 The history_* and planet_* table groups are composed of node, way, relation, and changeset tables. These contain the primary OSM data types and an additional changeset corresponding to OSM edits for convenient access. These objects are encoded using the BigQuery GEOGRAPHY data type so that they can be operated upon with the built-in geography functions to perform geometry and feature selection, additional processing. Example analyses are given below. This dataset is part of a larger effort to make data available in BigQuery through the Google Cloud Public Datasets program . OSM itself is produced as a public good by volunteers, and there are no guarantees about data quality. Interested in learning more about how these data were brought into BigQuery and how you can use them? Check out the sample queries below to get started. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .