This project focuses on developing a machine learning-driven system to classify hospital claims and treatment outcomes, offering a second opinion on healthcare costs and decision-making for insurance claims and treatment efficacy.Key Features and Tools:Machine Learning Algorithms: Leveraging Python (pandas, numpy, scikit-learn) for predictive modeling to assess claim validity and treatment outcomes.APIs Integration: Used Google Maps API to retrieve and map the locations of private hospitals in Malaysia.GIS Mapping Dashboard: Created a GIS-enabled dashboard in Microsoft Power BI to visualize private hospital distribution across Malaysia, aiding healthcare planning and analysis.Advanced Analytics Tools: Integrated Microsoft Excel, Python, and Google Collab for data processing and automation workflows.

Section and Beat Outline for Power BI maps

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.

The San Bernardino County CAASPP & ELPAC Report provides an overview of the county's performance. This interactive tool has seven reports that can be viewed by district, student group and grade level. In order to protect student confidentiality, no scores are reported (or included in the research files) for any group of 10 or fewer students.

Source: California Department of Education, CAASPP Research Files, https://caaspp-elpac.ets.org/caaspp/

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

Riyadh Metro Stations Dataset

Dataset Overview

This dataset contains information about metro stations in Riyadh, Saudi Arabia. It includes details such as station names, types, ratings, and geographic coordinates. The dataset is valuable for transportation analysis, urban planning, and navigation applications.

Dataset Contents

The dataset consists of the following columns:

Potential Use Cases

• Urban Mobility Analysis: Study metro station distribution and accessibility.
• Transportation Planning: Analyze station usage based on ratings and reviews.
• Navigation & Mapping: Enhance public transit applications with station locations.
• Service Optimization: Identify areas needing better metro services.

How to Use

1. Load the dataset into a data analysis tool like Python (pandas), R, or Excel.
2. Filter or group data based on ratings, locations, or number of reviews.
3. Use visualization tools like matplotlib, seaborn, or Power BI for insights.
4. Integrate with GIS software for geospatial mapping.

License & Acknowledgments

• Data sourced from publicly available platforms.
• This dataset is open for non-commercial research and analysis purposes.
• Proper attribution is required when using this dataset in research or publications.

Contact Information

For questions or collaboration, reach out via Kaggle comments or email.

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. .

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

This is a PowerBI Dashboard, to access this tool you will need to follow this url: https://app.powerbi.com/groups/me/reports/5614e2d7-ac65-4048-a5bc-d951bd906c46/ReportSection?experience=power-biTo access this tool:Login using your PowerBI login; or if you do not already have an accountRequest login details from datainsight@tfwm.org.uk; providing the name of the catalogue item and your justification for use of the requested item.Monthly usage statistics for the RTCC Pulse Report Dashboard. These statistics include the number and individual users who have viewed the RTCC Pulse Report dashboard, including the number of views per dashboard page Monthly trend comparison in user count, total page views and total report views are included for the previous reporting month.

PUG Workflow for adding external content to Operations Dashboard - Charts, Video, PowerBI and more provided by BP Geospatial Team

A document link providing access to the Data Dashboard (PowerBI) produced by the City of Vancouver Economic Prosperity and Housing Department. 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.

The Dashboard contains the following information:CPI (Consumer Price Index) Inflation Rate (Region, Year, Month, Topic (product))PPI (Production Price Index) Inflation Rate (Region, Year, Month, Topic (product))CPI & PPI Monthly Rate (Region, Year, Topic (product))Data from DEDAT Annual Report using IHS data.Dynamic dashboard reflecting the Outcome Indicator Release - Outcome Indicator: 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 Date10 October 2022LineageData 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:1. Real regional GDP growth rate per province2. The total GDP of the Western Cape in Rands3. The percentage contribution of provincial GDP to the country's GDP4. Percentage contribution of each industry to total GDPR of the Western CapeData Sources:DEDAT Annual Report (using IHS Data)Lineage:Data 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 Cap