The CDPHE Respiratory Virus Immunization Data (Tableau Dashboard) dataset contains 2024-2025 COVID-19, Influenza, and RSV immunization data that have been administered to Colorado residents and reported to the Colorado Immunization Information System. The data in this file updates each Wednesday and includes the following fields:category: County, Demographics, Statewidesub_category: Age Group, Race/Ethnicity, Sex level: Current or Time Trendage_breakout: 0-7mo, 8-19mo, 6mo-17yr, 18-64, 60-74, 65+, 75+, Alldate: date for published data value (rate)vaccine: COVID-19, Flu, Nirsevimab, RSVmetric: context for published data value (rate)ratepublish_date: Data that this dataset was published to the CDPHE Open Data PortalFor more information, data definitions, and context, please visit the CDPHE Respiratory Virus Immunization Data website (https://cdphe.colorado.gov/respiratory-virus-immunization-data).

The global field data collection software market is experiencing robust growth, driven by the increasing need for efficient data management across diverse sectors. The market's expansion is fueled by several key factors: the rising adoption of mobile technologies and cloud-based solutions for improved data accessibility and real-time analysis; the increasing demand for automation in data collection processes to reduce manual errors and improve productivity; and the growing emphasis on data-driven decision-making across industries such as construction, environmental monitoring, and oil and gas. This shift towards digitalization is transforming traditional fieldwork practices, leading to enhanced accuracy, reduced operational costs, and improved overall efficiency. We estimate the market size in 2025 to be approximately $2.5 billion, with a Compound Annual Growth Rate (CAGR) of 15% projected through 2033. This growth is expected to be further fueled by advancements in AI and machine learning, which enhance data analysis capabilities and provide valuable insights from collected field data. While challenges remain, including concerns regarding data security and integration with existing systems, the overall market outlook remains positive, with significant opportunities for software vendors and service providers. The market segmentation reveals significant opportunities across various applications and deployment types. The cloud-based segment is experiencing the fastest growth, driven by its scalability, accessibility, and cost-effectiveness. The construction, environmental monitoring, and oil and gas sectors are major consumers of field data collection software, demonstrating a strong demand for solutions that streamline workflows, enhance safety protocols, and optimize resource allocation. Geographic analysis suggests North America and Europe are currently the largest markets, although the Asia-Pacific region is expected to witness substantial growth in the coming years due to increasing infrastructure development and industrialization. The competitive landscape is dynamic, with both established players and emerging startups offering specialized solutions. The success of these companies hinges on their ability to provide robust, user-friendly software with strong integration capabilities and advanced analytical features.

The population of Metro Vancouver (20110729Regional Growth Strategy Projections Population, Housing and Employment 2006 – 2041 File) will have increased greatly by 2040, and finding a new source of reservoirs for drinking water (2015_ Water Consumption_ Statistics File) will be essential. This issue of drinking water needs to be optimized and estimated (Data Mining file) with the aim of developing the region. Three current sources of water reservoirs for Metro Vancouver are Capilano, Seymour, and Coquitlam, in which the treated water is being supplied to the customer. The linear optimization (LP) model (Optimization, Sensitivity Report File) illustrates the amount of drinking water for each reservoir and region. In fact, the B.C. government has a specific strategy for the growing population till 2040, which leads them toward their goal. In addition, another factor is the new water source for drinking water that needs to be estimated and monitored to anticipate the feasible water source (wells) until 2040. As such, the government will have to make a decision on how much groundwater is used. The goal of the project is two steps: (1) an optimization model for three water reservoirs, and (2) estimating the new source of water to 2040.

The process of data analysis for the project includes: the data is analyzed with six software—Trifacta Wrangler, AMPL, Excel Solver, Arc GIS, and SQL—and is visualized in Tableau. 1. Trifacta Wrangler Software clean data (Data Mining file). 2. AMPL and Solver Excel Software optimize drinking water consumption for Metro Vancouver (data in the Optimization and Sensitivity Report file). 3. ArcMap collaborates the raw data and result of the optimization water reservoir and estimating population till 2040 with the ArcGIS software (GIS Map for Tableau file). 4. Visualizing, estimating, and optimizing the source of drinking water for Metro Vancouver until 2040 with SQL software in Tableau (export tableau data file).

Per California Water Code Section 10609.80 (a), DWR has released an update to the indicators analyzed for the rural communities water shortage vulnerability analysis and a new interactive tool to explore the data. This page remains to archive the original dataset, but for more current information, please see the following pages: - https://water.ca.gov/Programs/Water-Use-And-Efficiency/SB-552/SB-552-Tool - https://data.cnra.ca.gov/dataset/water-shortage-vulnerability-technical-methods - https://data.cnra.ca.gov/dataset/i07-water-shortage-vulnerability-sections - https://data.cnra.ca.gov/dataset/i07-water-shortage-social-vulnerability-blockgroup This dataset is made publicly available pursuant to California Water Code Section 10609.42 which directs the California Department of Water Resources to identify small water suppliers and rural communities that may be at risk of drought and water shortage vulnerability and propose to the Governor and Legislature recommendations and information in support of improving the drought preparedness of small water suppliers and rural communities. As of March 2021, two datasets are offered here for download. The background information, results synthesis, methods and all reports submitted to the legislature are available here: https://water.ca.gov/Programs/Water-Use-And-Efficiency/2018-Water-Conservation-Legislation/County-Drought-Planning Two online interactive dashboards are available here to explore the datasets and findings. https://dwr.maps.arcgis.com/apps/MapSeries/index.html?appid=3353b370f7844f468ca16b8316fa3c7b The following datasets are offered here for download and for those who want to explore the data in tabular format. (1) Small Water Suppliers: In total, 2,419 small water suppliers were examined for their relative risk of drought and water shortage. Of these, 2,244 are community water systems. The remaining 175 systems analyzed are small non-community non-transient water systems that serve schools for which there is available spatial information. This dataset contains the final risk score and individual risk factors for each supplier examined. Spatial boundaries of water suppliers' service areas were used to calculate the extent and severity of each suppliers' exposure to projected climate changes (temperature, wildfire, and sea level rise) and to current environmental conditions and events. The boundaries used to represent service areas are available for download from the California Drinking Water System Area Boundaries, located on the California State Geoportal, which is available online for download at https://gispublic.waterboards.ca.gov/portal/home/item.html?id=fbba842bf134497c9d611ad506ec48cc (2) Rural Communities: In total 4,987 communities, represented by US Census Block Groups, were analyzed for their relative risk of drought and water shortage. Communities with a record of one or more domestic well installed within the past 50 years are included in the analysis. Each community examined received a numeric risk score, which is derived from a set of indicators developed from a stakeholder process. Indicators used to estimate risk represented three key components: (1) the exposure of suppliers and communities to hazardous conditions and events, (2) the physical and social vulnerability of communities to the exposure, and (3) recent history of shortage and drought impacts. The unit of analysis for the rural communities, also referred to as "self-supplied communities" is U.S. Census Block Groups (ACS 2012-2016 Tiger Shapefile). The Census Block Groups do not necessarily represent socially-defined communities, but they do cover areas where population resides. Using this spatial unit for this analysis allows us to access demographic information that is otherwise not available in small geographic units.

Detroit Health Departments COVID-19 Dashboard that tracks cases and deaths over time, demographics, testing, hospital capacity, zip code level information, nursing home cases and deaths, and vaccination breakdowns.

Tableau de bord de la situation COVID-19 de l'OMS

Analysis of ‘COVID-19 Coronavirus Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/vignesh1694/covid19-coronavirus on 14 February 2022.

--- Dataset description provided by original source is as follows ---

Context

A SARS-like virus outbreak originating in Wuhan, China, is spreading into neighboring Asian countries, and as far afield as Australia, the US a and Europe.

On 31 December 2019, the Chinese authorities reported a case of pneumonia with an unknown cause in Wuhan, Hubei province, to the World Health Organisation (WHO)’s China Office. As more and more cases emerged, totaling 44 by 3 January, the country’s National Health Commission isolated the virus causing fever and flu-like symptoms and identified it as a novel coronavirus, now known to the WHO as 2019-nCoV.

The following dataset shows the numbers of spreading coronavirus across the globe.

Content

Sno - Serial number Date - Date of the observation Province / State - Province or state of the observation Country - Country of observation Last Update - Recent update (not accurate in terms of time) Confirmed - Number of confirmed cases Deaths - Number of death cases Recovered - Number of recovered cases

Acknowledgements

Thanks to John Hopkins CSSE for the live updates on Coronavirus and data streaming. Source: https://github.com/CSSEGISandData/COVID-19 Dashboard: https://public.tableau.com/profile/vignesh.coumarane#!/vizhome/DashboardToupload/Dashboard12

Inspiration

Inspired by the following work: https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

--- Original source retains full ownership of the source dataset ---

This dashboard is hosted on Tableau Public, and was created from ONS data on annual internal migration flows between local authorities.This data was then processed to show net flows, and visualised with GIS data to create the dashboard.

Rocky Mountain Institute (RMI) Transportation Electrification Strategy (TES) Electric Vehicle Charging Station Layer displaying modeled need for EV stations by County within Washington State (2023-2035).The RMI TES Modeled Need layer is based on 2010 Counties from the U.S. Census Bureau.GridUp Tool: GridUp ToolTableau Data: https://public.tableau.com/app/profile/waevcouncil/viz/WashingtonTransportationElectrificationStrategy/Story_PublishedPlease direct questions about this item to partnerships@wsdot. If you are having trouble viewing this item, please email OnlineMapSupport@wsdot.wa.gov.

Analysis of ‘Evaluation- Extinction Eclairage public-questionnaires’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/618b4485a6250e58275506ce on 15 January 2022.

--- Dataset description provided by original source is as follows ---

Les données publiées sur l'expérimentation de l'extinction de l'éclairage public sont celles issues du questionnaire auprès des habitants réalisé dans les quartiers concernés Le Pâtis, les Couronneries, Beaulieu, La cité des 7 villes de mi Mai 2021 à mi Juin 2021.

Afin d'en faciliter la lecture, la ville de Poitiers vous propose un tableau de bord de valorisation de ces données

--- Original source retains full ownership of the source dataset ---

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Cet ensemble de données comprend la version Excel du Tableau 2.1 (Projections pour les précipitations extrêmes fondées sur de multiples méthodes) du rapport « Projections climatiques pour la région de la capitale nationale » (2020). Cette version du tableau comprend les trois horizons projectionnels (années 2030, 2050 et 2080).

Exactitude: Les mises en garde propres à l'indice sont précisées dans le rapport.

Fréquence des mises à jour: Téléversement ponctuel (2020)

Source d'information: Constatations recueillies pendant le projet

Courriel de l'auteur: Unité des changements climatiques et de la résilience

Classe d'entité localisant les parkings sur le territoire de la Métropole Toulon Provence Méditerranée (parking de surface, parking relais, parking en ouvrage / gratuit, payant, zone bleue, réglementé).

Visualiser une réutilisation des données par la Métropole TPM :

- Tableau de bord sur ...

Aux termes de l'article 37 de la loi n° 2019-828 du 06 août 2019 de transformation de la fonction publique, les régions, les départements, les collectivités territoriales de plus de 80 000 habitants, les établissements publics de coopération intercommunale à fiscalité propre de plus de 80 000 habitants publient chaque année, sur leur site internet, la somme des dix rémunérations les plus élevées des agents relevant de leur périmètre, en précisant également le nombre de femmes et d'hommes figurant parmi ces dix rémunérations les plus élevées.

The FY2020 DCPS School-level Budgets: FY20 Proposed (Mayoral Submission) vs FY19 Approved Dashboard was developed by the Budget Office and is an interactive data visualization tool, built in Tableau, that allows users to view the Mayor’s proposed FY20 budget released on March 20, 2019 for individual District of Columbia Public Schools’ (DCPS) school-level budgets. Users are able to select individual DCPS schools and a school-wide summary to compare the Mayor’s proposed FY20 budget versus FY19 approved budget for the first two tabs. This dashboard blends data from the District’s official financial system. Audited enrollment data was obtained from the Office of the State Superintendent of Education (OSSE). Visit the DC Council Office of the Budget Director website for further documentation.

Climate change is one of the great threats our natural world faces today, so why doesn’t the U.S. government track greenhouse gas emissions from federal fossil fuel production that occurs on public lands? The lack of effort to record and understand climate emissions is astounding given that the federal government is one of the largest energy asset managers in the world. Limited data leaves Americans, the owners of public lands and shareholders of federal energy resources, in the dark on the extent to which fossil fuel emissions from public lands are contributing to rising global temperatures. In absence of government oversight, The Wilderness Society has started to track and calculate emissions data, using various government sources, including data from the Office of Natural Resources Revenues (ONRR) and US Extractive Industries Transparency Initiative (USEITI).What we found was staggering. Among the results:Greenhouse gas emissions associated with oil, gas, and coal from public lands are equivalent to one-fifth or more of total US emissions. If U.S. public lands were their own country, they would rank 5th in the world for greenhouse gas emissionsOur accompanying report In The Dark: The hidden climate impacts of energy develop on public lands also explains more about why the federal government needs to inform its shareholders (the American people) when managing their assets (energy resources on public lands) .

Rocky Mountain Institute (RMI) Transportation Electrification Strategy (TES) Electric Vehicle Charging Station Layers displaying modeled need for EV stations within Washington State (2023-2035).The RMI TES Modeled Need layer is based on 2010 Census Block Groups from the U.S. Census Bureau.GridUp Tool: GridUp ToolTableau Data: https://public.tableau.com/app/profile/waevcouncil/viz/WashingtonTransportationElectrificationStrategy/Story_PublishedREST URL: https://services.arcgis.com/IYrj3otxNjPsrTRD/arcgis/rest/services/RMI_TES/FeatureServerPlease direct questions about this item to partnerships@wsdot. If you are having trouble viewing this item, please email OnlineMapSupport@wsdot.wa.gov.

Rocky Mountain Institute (RMI) Transportation Electrification Strategy (TES) Electric Vehicle Charging Station Layers displaying modeled need for EV stations within Washington State (2023-2035).The RMI TES Modeled Need layer is based on 2010 Counties from the U.S. Census Bureau.GridUp Tool: GridUp ToolTableau Data: https://public.tableau.com/app/profile/waevcouncil/viz/WashingtonTransportationElectrificationStrategy/Story_PublishedPlease direct questions about this item to partnerships@wsdot. If you are having trouble viewing this item, please email OnlineMapSupport@wsdot.wa.gov.

Le tableau de état des zones de récolte d’appâts est un tableau connexe à celui de la zone de récolte d’appâts. Pour plus de détails et de métadonnées, consultez la zone de récolte d’appâts.Personne-resourceMae Rannells-Warren, Section des pêches, Direction des politiques relatives au poisson et à la faune, mae.rannells-warren@ontario.ca