Web map created by Research and Stats for PowerBi DashboardMap of Current Sales and Use Tax Rates

This Power BI dashboard shows the COVID-19 vaccination rate by key demographics including age groups, race and ethnicity, and sex for Tempe zip codes.Data Source: Maricopa County GIS Open Data weekly count of COVID-19 vaccinations. The data were reformatted from the source data to accommodate dashboard configuration. The Maricopa County Department of Public Health (MCDPH) releases the COVID-19 vaccination data for each zip code and city in Maricopa County at ~12:00 PM weekly on Wednesdays via the Maricopa County GIS Open Data website (https://data-maricopa.opendata.arcgis.com/). More information about the data is available on the Maricopa County COVID-19 Vaccine Data page (https://www.maricopa.gov/5671/Public-Vaccine-Data#dashboard). The dashboard’s values are refreshed at 3:00 PM weekly on Wednesdays. The most recent date included on the dashboard is available by hovering over the last point on the right-hand side of each chart. Please note that the times when the Maricopa County Department of Public Health (MCDPH) releases weekly data for COVID-19 vaccines may vary. If data are not released by the time of the scheduled dashboard refresh, the values may appear on the dashboard with the next data release, which may be one or more days after the last scheduled release.Dates: Updated data shows publishing dates which represents values from the previous calendar week (Sunday through Saturday). For more details on data reporting, please see the Maricopa County COVID-19 data reporting notes at https://www.maricopa.gov/5460/Coronavirus-Disease-2019.

This point layer represents the water quality stations located throughout the San Antonio River Basin. The San Antonio River Authority's environmental science departments monitors and collects surface water samples at these locations. Samples are processed immediately at our in-house Texas Commission on Environmental Quality (TCEQ) accredited Lab. This layer was created to share externally through the SA River Authority Open Data Portal. It is also made visible through our Water Quality Viewer, Power BI embedded dashboard. This data is subject to change. Last updated on 3/22/2021.Here are the fields available in this layer: station_idsubwatershed_namesara_short_descounty_namesegement_idlatitudelongitudewaterbody_namewatershed_namestation_type

Data is sourced from various health resources. Data is transformed into a BI format and quality assured. Data is consumed by a dashboard created in Power BI. Four reports exist for this dashboard:1. HIV Prevalence and TB Success RateHIV prevalence amongst women attending antenatal clinics in the Western Cape (2012-2015) by district and yearHIV prevalence amongst women attending antenatal clinics in the province (2012-2015) by province and yearTB Programme Success Rate (2013/14-2018/19) by TB Measure2. Births and Maternal MortalitiesNeonatal in facility (0-28 days) mortality rate (2015/16-2018/19); by years and neonatal death rate in facility and mortality rate by 1,000 live births Facility maternal mortality rate (2002, 2005, 2008, 2011, 2014); by triennia (3 years) deaths by 1,000 live births in WC (incl count of maternal deaths, count of live births, and infant maternal mortality ration)(Child (under 5) and Infant (under 1) mortality rate (2011, 2012, 2013); filter years, Infant/Child age band; Years, District, Births and Deaths by age bandDelivery rate in facility to women under 20 years (2013/14-2018/19); filter by financial year (FY); delivery rate by FY, delivery rate, numerator (births to women <20), denominator (total births)3. Deaths and Life ExpectancyLeading underlying causes of death in the Western Cape (2012-2016) by years and cause of deathYears of life lost (YLL) by cause of death in the WC (2012-2016) by years and YLL cause of deathAverage Life Expectency (LE) at birth (2006, 2011, 2016) by year, province, and gender4. Travel time to facilitiesTravel time taken to health facility by households with expenditure less than R1200-SA (2013-2018); by year, province, and travel time to health facilityTravel time taken to health facility by households with expenditure less than R1200-WC (2013-2018); by year, province, population group, and travel time to health facilityPublication Date2 September 2021LineageData from various sources transformed to a BI format and used to develop dynamic Power BI dashboards reflecting Outcome Indicators: HIV prevalence amongst women attending antenatal clinics in the provinceAll DS-TB (drug-susceptible tuberculosis) client treatment success rateNeonatal in facility (0-28 days) mortality rateFacility maternal mortality rateDelivery rate in facility to women under 20 yearsLife Expectancy (LE)Leading underlying causes of death in the Western CapeTravel time taken to health facility by households with expenditure less than R1200 (SA and WC)Data Source2019 National Antenatal Sentinel HIV Survey, National Department of Health 2021;Annual report 2014/15-2020/21, DOH;District Health Information Systems;Mid-year population estimates, Stats SA; Life Expectancy Stats SA calculations;Mortality and Causes of Death in South Africa 2018, June 2021, Stats SA

Data is sourced from Stats SA Data is transformed into a BI format and quality assured. Data is consumed by a dashboard created in Power BI. The following reports exist for this dashboard:Percentage Agriculture GDP growth (2015-2019); filter by year and region - constant value growth rate by year and regionPercentage contribution to provincial GDP (2015-2019); filter by year and region - constant value contribution by year and regionPercentage contribution to agriculture employment (2015-2019); filter by year and quarter - % contribution by year and quarterPublication Date20 January 2023LineageData from Statistics South Africa is sourced, transformed into a BI format and then dynamic dashboard reflecting the Outcome Indicators are developed using Power BI: Percentage agricultural growth ratePercentage contribution of agriculture to provincial GDPPercentage contribution of agriculture to total employment in Western CapeData SourceGDP 2015-2020, Stats SAQLFS 2017 - 2021, Stats SA

Market Overview: The global geospatial solutions market is projected to reach a valuation of $438.15 billion by 2033, growing at a robust CAGR of 14.6% from 2025 to 2033. This growth is driven by increasing urbanization, rising demand for real-time location-based services, advancements in sensor technologies, and government initiatives promoting smart infrastructure. The market is segmented based on technology (GIS/Geospatial Analytics, Remote Sensing, GPS, 3D Scanning), component (Hardware, Software, Services), application (Surveying & Mapping, Geovisualization, Planning & Analysis, Land Management), end use (Utility, Business, Transportation, Defense & Intelligence, Infrastructure Development, Natural Resources), and region. Key Trends and Challenges: The adoption of cloud-based geospatial solutions is a major trend, enabling cost-effective access to data and services. Artificial intelligence (AI) and machine learning (ML) are also gaining prominence, enhancing data analysis and decision-making. However, challenges include data interoperability, data security concerns, and the need for skilled professionals. The market is fragmented, with established vendors such as Microsoft, Google, and Trimble coexisting with innovative startups. Government initiatives and partnerships with private companies are expected to foster market growth. Key regions include North America, Europe, and Asia Pacific, with emerging markets in Latin America and the Middle East offering significant growth potential. Recent developments include: In July 2024, Esri collaborated with Microsoft Corporation to integrate its spatial analytics technology with Fabric, Microsoft's unified analytics SaaS platform. Data experts, including analysts, data scientists, engineers, and executives, could seamlessly use Esri's advanced spatial analytics tools and visualizations within Microsoft Fabric through this integration. This collaboration enabled powerful spatial analytics to be easily shared across organizational tools such as Microsoft Fabric, Power BI, and Esri's ArcGIS environment. , In February 2024, GE Vernova announced the release of Proficy for Sustainability Insights, a new AI-based software solution aimed at helping manufacturers achieve sustainability goals while maximizing productivity and profitability. The software integrates operational and sustainability data, enabling industrial companies to use resources more efficiently and manage climate metrics required for regulatory compliance across plants or enterprises. .

Socio-economic dashboard depicting Employment and Job Creation. Unemployment Rate (Province, Year, Qtr, Rate [percentage])Unemployment Rate by population group (Province, Year, Population Group, Rate [percentage])Unemployment Rate by gender (Province, Year, gender, Rate [percentage])Youth Unemployment Rate (Province, Year, Age cohorts, Rate [percentage])% Employment in formal and informal sectors (Province, Year, Sectors incl Agriculture, Sectors excl Agriculture, Private Households (domestic work), Rate [percentage])Labour particpation Rate (Province, Year, labour particpation Rate [percentage])Publication Date13 March 2022LineageData is sourced from Stats SA Quarterly Labour Force Surveys. Data is transformed into a BI format and quality assured. Data is consumed by a dashboard created in Power BI. Six reports exist for this dashboard:Unemployment RateUnemployment Rate by population groupUnemployment Rate by genderYouth Unemployment Rate % Employment in formal and informal sectorsLabour particpation RateData SourceData from Stats SA; Labour force surveys and Quarterly Labour Force Surveys 2017 – 2021Dynamic dashboard reflecting the Outcome Indicator Release - Outcome Indicator: Unemployment rateUnemployment rate by population in WCUnemployment rate by gender in WCYouth unemployment ratePercentage of employed people working in the informal sector, including domestic work in WCLabour participation rate

This dataset is of 2017 properties. It is used for the City's Power BI training.

Link to the City of O'Fallon's Power BI Budget Report. This is not a live report - data is generally at least one business day behind actual.

Section and Beat Outline for Power BI maps

A Microsoft PowerBI Dashboard published by the City of Vancouver's Finance Department. Updated daily from figures in the City's Workday system.

The Dashboard contains the following information:Population by province (9 SA provinces), age and genderWC Population by gender, age cohorts, and district and metroNational population as a tree chart (and map)Decomposition tree by gender and age cohortData from 2002-2021 - using Census data, Community Survey 2016, and mid-year population esitmatesDynamic dashboard reflecting the Outcome Indicator Release - Outcome Indicator: The Western Cape population by age group and genderThe Western Cape District population by age group and genderThe South African population per provincePublication Date1 September 2022Lineage:Data is sourced from Statistics South Africa. Data is transformed into a BI format and quality assured. Data is consumed by a dashboard created in Power BI. Four reports exist for this dashboard:Population by age and genderWestern Cape PopulationNational PopulationDecomposition TreeData SourceMid-year population estimates - Stats SA (2002-2021)

This hosted feature layer has been developed in-house by the VDOT CO TED Highway Safety section for crash analysis purpose based on updates from the Power BI Crash Tool. The Crash Data Dictionary can be found here. The main source of the data is owned and maintained by DMV. In providing this web map, we assume no responsibility for the accuracy and completeness of the data. In the process of recording and compiling the data, some deletions and/or omissions of data may occur and VDOT is not responsible for any such occurrences.

The main source of the data is owned and maintained by DMV. In providing this tool, VDOT assumes no responsibility for the accuracy and completeness of the data. In the process of recording and compiling the data, some deletions and/or omissions of data may occur and VDOT is not responsible for any such occurrences. The most recent data contained in this report is preliminary and subject to change. Please be advised that, under Title 23 United State Code – Section 409, this crash information cannot be used in discovery or as evidence in a Federal or State court proceeding or considered for other purposes in any action for damages against VDOT or the State of Virginia arising from any occurrence at the location identified.

All users shall comply with and be subject to all applicable laws and regulations, whether federal or state, in connection with any of the receipt and use of DMV data including, but not limited to, (1) the Federal Drivers Privacy Protection Act (18 U.S.C. § 2721 et seq.), (2) the Government Data Collection and Dissemination Practices Act (Va. Code § 2.2-3800 et seq.), (3) the Virginia Computer Crimes Act (Va. Code § 18.2-152.1 et seq.), (4) the provisions of Va. Code §§ 46.2-208 and 58.1-3, and (5) any successor rules, regulations, or guidelines adopted by DMV with regard to disclosure or dissemination of any information obtained from DMV records or files.

Data is sourced from Stats SA General Household Survey. Data is transformed into a BI format and quality assured. Data is consumed by a dashboard created in Power BI. Four reports exist for this dashboard:1. Household access to basic services (Lighting, Sanitation (type), Piped Water, Refuse removal) by year and province (2013-2018).Percentage households accessing electricity for lighting (by sources); filter by year and province (2013-2018)Percentage households accessing sanitation (by type); filter by year and province (2013-2018)Percentage households accessing piped water (by water source); filter by year and province (2013-2018)Percentage households accessing sanitation (by type) by year and province (2013-2018)2. Percentage households in formal and informal dwellings by province by year (2016-2020)Formal and informal dwellings by year and province as percentage Households that are child-headed households by year, province, and age cohorts (<18, 18-20, >20) as count and percentagePercentage households with expenditure below R1,200; filter by year, province, and spend cohort (

This hosted feature layer has been developed in-house by the VDOT CO TED Highway Safety section for crash analysis purpose based on updates from the Power BI Crash Tool. The Crash Data Dictionary can be found here. The main source of the data is owned and maintained by DMV. In providing this web map, we assume no responsibility for the accuracy and completeness of the data. In the process of recording and compiling the data, some deletions and/or omissions of data may occur and VDOT is not responsible for any such occurrences.

The main source of the data is owned and maintained by DMV. In providing this tool, VDOT assumes no responsibility for the accuracy and completeness of the data. In the process of recording and compiling the data, some deletions and/or omissions of data may occur and VDOT is not responsible for any such occurrences. The most recent data contained in this report is preliminary and subject to change. Please be advised that, under Title 23 United State Code – Section 409, this crash information cannot be used in discovery or as evidence in a Federal or State court proceeding or considered for other purposes in any action for damages against VDOT or the State of Virginia arising from any occurrence at the location identified.

All users shall comply with and be subject to all applicable laws and regulations, whether federal or state, in connection with any of the receipt and use of DMV data including, but not limited to, (1) the Federal Drivers Privacy Protection Act (18 U.S.C. § 2721 et seq.), (2) the Government Data Collection and Dissemination Practices Act (Va. Code § 2.2-3800 et seq.), (3) the Virginia Computer Crimes Act (Va. Code § 18.2-152.1 et seq.), (4) the provisions of Va. Code §§ 46.2-208 and 58.1-3, and (5) any successor rules, regulations, or guidelines adopted by DMV with regard to disclosure or dissemination of any information obtained from DMV records or files.

This data layer is a draft of selected species ranges from ECOS. The layer has to be made public to test for integration into a Power BI dashboard. Please do not use for any other purposes. Most current geospatial data including area of influence, current and historical ranges, data are available through the Threatened and Endangered Species System (TESS) here. https://ecos.fws.gov/tess/speciesModule/home.doOther information may be found on the FWS Endangered Species web page here https://www.fws.gov/program/endangered-species

The River Authority Water Quality Viewer is a tabbed web mapping application. The following tabs are defined below:The first tab - Water Quality – is an embedded interactive Power BI dashboard. It displays monitoring efforts for the Texas Commission on Environmental Quality’s (TCEQ) Clean Rivers Program and summarizes how the water quality in the San Antonio River Basin compares to the Texas Surface Water Quality Standards (TSWQS) using the latest TCEQ Integrated Report assessment. Through the Texas Clean Rivers Program, The River Authority and its partners collect surface water, stormwater and sediment chemistry, physical, and biological data within the San Antonio River Basin. The second tab – Primary Contact Recreation Use –summarizes assessment outcomes for the San Antonio River Watershed as identified in the Texas Commission on Environmental Quality (TCEQ) 2018, 2016, 2014, and 2012 Integrated Report (IR). It displays the Primary Contact Recreation Use Designations by color.The third tab – Aquatic Life Use – summarizes assessment outcomes for the San Antonio River Watershed as identified in the Texas Commission on Environmental Quality (TCEQ) 2018, 2016, 2014, and 2012 Integrated Report (IR). This Web Map displays the Aquatic Life Use Designations. It is the dependent of the SARA Water Quality Viewer and uses the Aquatic Life Use Web Map.The fourth tab – General Use – summarizes assessment outcomes for the San Antonio River Watershed as identified in the Texas Commission on Environmental Quality (TCEQ) 2016, 2014, and 2012 Integrated Report (IR). It displays the General Use Designations. It is the dependent of the SARA Water Quality Viewer and uses the General Use Web Map.The fifth tab – Fish Consumption Use – summarizes assessment outcomes for the San Antonio River Watershed as identified in the Texas Commission on Environmental Quality (TCEQ) 2016, 2014, and 2012 Integrated Report (IR). This Web Map displays the Fish Consumption Use Designations. It is the dependent of the Fish Consumption Use Tab and the SARA Water Quality Viewer.Please do not delete or modify The River Authority GISESD

The dashboard contains the following economic information:Real regional GDP Growth rate (Year, Region / Province)Total GDP in WC by Rands (Year, Region, Constant/Current amount)WC as % contribution to SA's GDP (Year, Region, Constant/Current value)% contribution by industry to total GDP (Year, Region, Industry)Dynamic dashboard reflecting the Outcome Indicator Release - Outcome Indicators: Real regional GDP growth rate per provinceThe total GDP of the Western Cape in RandsThe percentage contribution of provincial GDP to the country's GDPPercentage contribution of each industry to total GDPR of the Western CapePublication Date17 November 2021Data SourceDEDAT Annual Report (using IHS Data)LineageData is sourced from DEDAT reports using IHS data. Data is transformed into a BI format and quality assured. Data is consumed by a dashboard created in Power BI. Four reports exist for this dashboard:Real regional GDP growth rate per provinceThe total GDP of the Western Cape in RandsThe percentage contribution of provincial GDP to the country's GDPPercentage contribution of each industry to total GDPR of the Western Cape

A data dashboard in the form of a document link to Microsoft Power BI Dashboard of the same name, prepared and maintained by the Department of Economic Prosperity and Housing. Data is updated quarterly.NOTE: This product and the information shown is provided "AS IS" and exists for informational purposes only. The City of Vancouver (COV) makes no warranties regarding the accuracy of such data. This product and information is not prepared, nor is suitable, for legal, engineering, or surveying purposes. Any sale, reproduction or distribution of this information, or products derived therefrom, in any format is expressly prohibited. Data are provided by multiple sources and subject to change without notice.