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.

Tabular dataset for data analysis and machine learning practice. The dataset is about the market and is usable for Power BI practice and data science.

Explore the world of data visualization with this Power BI dataset containing HR Analytics and Sales Analytics datasets. Gain insights, create impactful reports, and craft engaging dashboards using real-world data from HR and sales domains. Sharpen your Power BI skills and uncover valuable data-driven insights with this powerful dataset. Happy analyzing!

📊 Bellabeat Case Study – Power BI Dashboard & Dataset

📌 Overview

This dataset contains the Power BI dashboard file and supporting cleaned datasets used in the Bellabeat case study.
It is intended for data analysis, visualization, and health trend insights.

📂 Files Included

• bellabeat_dashboard.pbix → Interactive Power BI dashboard
• cleaned_daily_activity.csv → Processed daily activity data
• cleaned_hourly_steps.csv → Processed hourly step data
• cleaned_hourly_intensities.csv → Processed hourly intensities data
• cleaned_minuteSleep.csv → Processed sleep data
• cleaned_weight_log.csv → Processed weight_log data
• fact_sleep_daily.csv → Daily aggregated data derived from cleaned_minuteSleep.csv

🎯 Objective

• To explore user activity and lifestyle trends.
• To design a business intelligence dashboard for Bellabeat, focusing on:
  • User engagement patterns
  • Sedentary lifestyle risks
  • Health & wellness insights

🔍 Data Source

The dataset is based on FitBit Fitness Tracker Data
- License: CC0: Public Domain
- Made available through Mobius
- Kaggle source: FitBit Fitness Tracker Dataset

📖 Inspiration

This project aims to analyze human temporal routines and behavioral patterns to support Bellabeat’s smart health product strategy.

🙏 Acknowledgements

Special thanks to the original researchers and the Kaggle community for providing starter notebooks and inspiration.

⚠️ Disclaimer

This dataset is for educational and portfolio purposes only and should not be considered medical advice.

The global data visualization market, valued at $9.84 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 10.95% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing volume and complexity of data generated across various industries necessitates effective visualization tools for insightful analysis and decision-making. Furthermore, the rising adoption of cloud-based solutions offers scalability, accessibility, and cost-effectiveness, driving market growth. Advances in artificial intelligence (AI) and machine learning (ML) are integrating seamlessly with data visualization platforms, enhancing automation and predictive capabilities, further stimulating market demand. The BFSI (Banking, Financial Services, and Insurance) sector, along with IT and Telecommunications, are major adopters, leveraging data visualization for risk management, fraud detection, customer relationship management, and network optimization. However, challenges remain, including the need for skilled professionals to effectively utilize these tools and concerns regarding data security and privacy. The market segmentation reveals a strong presence of executive management and marketing departments across organizations, highlighting the strategic importance of data visualization in business operations. The market's competitive landscape is characterized by established players like SAS Institute, IBM, Microsoft, and Salesforce (Tableau), along with emerging innovative companies. This competition fosters innovation and drives down costs, making data visualization solutions more accessible to a broader range of businesses and organizations. Regional variations in market penetration are expected, with North America and Europe currently holding significant shares, but Asia Pacific is poised for substantial growth, driven by rapid digitalization and technological advancements in the region. The on-premise deployment mode still holds a considerable market share, though the cloud/on-demand segment is experiencing faster growth due to its inherent advantages. The ongoing trend towards self-service business intelligence (BI) tools is empowering end-users to access and analyze data independently, increasing the overall market demand for user-friendly and intuitive data visualization platforms. Future growth will depend on continued technological advancements, expanding applications across diverse industries, and addressing the existing challenges related to data skills gaps and security concerns. This report provides a comprehensive analysis of the Data Visualization Market, projecting robust growth from $XX Billion in 2025 to $YY Billion by 2033. It covers the period from 2019 to 2033, with a focus on the forecast period 2025-2033 and a base year of 2025. This in-depth study examines key market segments, competitive landscapes, and emerging trends influencing this rapidly evolving industry. The report is designed for executives, investors, and market analysts seeking actionable insights into the future of data visualization. Recent developments include: September 2022: KPI 360, an AI-driven solution that uses real-time data monitoring and prediction to assist manufacturing organizations in seeing various operational data sources through a single, comprehensive industrial intelligence dashboard that sets up in hours, was recently unveiled by SymphonyAI Industrial., January 2022: The most recent version of the IVAAP platform for ubiquitous subsurface visualization and analytics applications was released by INT, a top supplier of data visualization software. IVAAP allows exploring, visualizing, and computing energy data by providing full OSDU Data Platform compatibility. With the new edition, IVAAP's map-based search, data discovery, and data selection are expanded to include 3D seismic volume intersection, 2D seismic overlays, reservoir, and base map widgets for cloud-based visualization of all forms of energy data.. Key drivers for this market are: Cloud Deployment of Data Visualization Solutions, Increasing Need for Quick Decision Making. Potential restraints include: Lack of Tech Savvy and Skilled Workforce/Inability. Notable trends are: Retail Segment to Witness Significant Growth.

This is essentially a power BI dashboard created using existing data. The actual data source is: https://www.kaggle.com/datasets/rohitsahoo/sales-forecasting

Learning Data Visualization Tools Market Outlook

According to our latest research, the global Learning Data Visualization Tools Market size reached USD 2.8 billion in 2024, demonstrating robust growth driven by the increasing demand for data literacy and analytics skills across various sectors. The market is expected to grow at a CAGR of 13.7% from 2025 to 2033, projecting a value of USD 8.8 billion by 2033. This surge is primarily attributed to the rapid digitization of education and corporate learning environments, the proliferation of big data, and the critical need for interactive, accessible analytical tools to foster effective data comprehension and decision-making.

One of the most significant growth factors for the Learning Data Visualization Tools Market is the widespread integration of data-driven decision-making processes within organizations and educational institutions. As businesses and academic settings increasingly rely on data to guide strategies, there is a parallel surge in the demand for professionals who possess strong data visualization skills. This has led to a marked increase in the adoption of user-friendly data visualization tools such as Tableau, Power BI, and Google Data Studio in both formal education and corporate training programs. The ability of these tools to simplify complex datasets into intuitive visual representations is a key driver, enabling learners to grasp intricate concepts more efficiently and apply them in real-world scenarios.

Technological advancements and the evolution of cloud-based learning platforms have further propelled the market. The shift toward digital and remote learning, especially post-pandemic, has accelerated the adoption of cloud-based data visualization tools, which offer scalability, accessibility, and seamless integration with other e-learning resources. Cloud deployment eliminates geographical barriers, allowing learners and organizations from diverse regions to access advanced visualization tools and resources at any time. Additionally, the increasing availability of free and open-source visualization libraries such as D3.js has democratized access to these technologies, further expanding the market’s reach across different socioeconomic segments.

Another crucial growth driver is the rising emphasis on upskilling and reskilling initiatives across industries. As automation and artificial intelligence reshape job requirements, data literacy has become a fundamental skill for both students and working professionals. Enterprises are investing heavily in learning platforms that incorporate data visualization tools to train their workforce, ensuring they remain competitive in the digital economy. The trend is mirrored in higher education, where curricula are being revamped to include data visualization modules, reflecting the growing recognition of its importance in fostering analytical and critical thinking skills among learners.

From a regional perspective, North America dominates the Learning Data Visualization Tools Market, accounting for the largest revenue share in 2024. This can be attributed to the presence of leading technology providers, a mature e-learning ecosystem, and high levels of digital adoption in both educational and corporate sectors. However, Asia Pacific is emerging as the fastest-growing region, driven by rapid digital transformation, government initiatives to enhance digital literacy, and the increasing penetration of internet and mobile devices. Europe also contributes significantly, with a strong focus on educational innovation and enterprise training. These regional dynamics are shaping the competitive landscape and driving the global expansion of learning data visualization tools.

Tool Type Analysis

The Tool Type segment of the Learning Data Visualization Tools Market is highly diverse, encompassing established platforms like Tableau, Power BI, and Qlik, as well as newer entrants such as Google Data Studio and open-source solutions like D3.js. Tableau remains a market leader due to its intuitive drag-and-drop interface, robust analytics capabilities, and widespread adoption in both academic and corporate settings. Its ability to handle large datasets and integrate seamlessly with various data sources makes it a preferred choice for institutions aiming to provide hands-on, practical training in data visualization. Power BI, backed by Microsoft’s ecosystem, is gaining significant traction, particularly among enterpr

The size of the Business Intelligence Market was valued at USD 33.12 Billion in 2024 and is projected to reach USD 70.38 Billion by 2033, with an expected CAGR of 11.37% during the forecast period. Recent developments include: January 2023: Microsoft unveiled Power BI enhanced experiences in Microsoft Teams in January 2023. The three new features announced are rich broadcasting cards for Conversation in Microsoft Teams and an upgrade for old Power BI tabs for taking notes and learning from experiences and needs., December 2022: Tableau 2022.4 was released in December 2022 for customers and researchers to explore information. It automates creating, analyzing, and communicating insights through data stories, including Data Change Radar, Information Guide, and Explaining the Viz., October 2022: Oracle increased inclusive and included data and analytics capabilities in October 2022 to empower business users. With the extra stuff in Oracle Fusion Analytics for ERP, CX, HCM, and SCM data analysis, business users can track performance against corporate objectives using visualizations, KPIs, and analytics.. Key drivers for this market are: Growing Volume of Data: The increasing generation of data from various sources drives the need for effective data management and analysis capabilities.

Demand for Real-Time Insights: Businesses require real-time data insights to make timely decisions and respond to market changes effectively.

Adoption of Cloud-Based Solutions: Cloud-based BI solutions offer flexibility, cost-effectiveness, and scalability, driving their adoption.. Potential restraints include: Data Security and Privacy Concerns: The handling and storage of sensitive data raise concerns about data breaches and privacy violations.

Integration Complexity: Integrating BI systems with other enterprise applications and data sources can be complex and time-consuming.

Skill Shortage: The lack of skilled professionals with expertise in data analysis and business intelligence poses a challenge.. Notable trends are: Cognitive BI: BI tools are incorporating cognitive technologies to automate data analysis and provide personalized insights.

Predictive Analytics: BI platforms are leveraging predictive analytics to anticipate future events and trends.

Self-Service BI: Self-service BI empowers business users to create their own reports and analyses without the need for technical assistance.

Natural Language Processing (NLP): NLP capabilities enable users to interact with BI tools using natural language queries..

Customer Segmentation Analysis 📌 Project Overview This project aims to analyze sales and customer segmentation data using an interactive Power BI dashboard. The analysis provides insights into total sales, customer distribution, education levels, language preferences, and state-wise segmentation, helping businesses make data-driven decisions.

📊 Dashboard Features The project includes two key dashboards:

1️⃣ Sales Segmentation Analysis Total Sales: 162M | Total Customers: 40K Sales Distribution by Gender, Year, and Preferred Language Education Level vs. Sales Contribution State-wise Total Sales and Performance Trends

2️⃣ Customer Segmentation Analysis Total Customer Distribution across Different Metrics Customer Demographics: Gender, Education Level, and Language Preference State-wise Customer Count

🛠️ Tech Stack & Tools Used Power BI – Data visualization and interactive dashboard creation Excel / CSV Dataset – Raw data source DAX & Power Query – Data transformation and calculated measures

📈 Key Insights & Findings Top-performing languages: Customers who speak German (26.95%) and French (24.9%) contribute the most to sales. Education Level Impact: Associate Degree holders generate the highest sales and customer count. State-wise performance: Lakshadweep, Himachal Pradesh, and Bihar are the top-performing states.

Comprehensive business intelligence analysis for Microsoft Power BI including financial metrics, founder insights, competitive positioning, and investment research. This dataset contains AI-powered analysis of leadership interviews, public content, and market intelligence for due diligence and competitive research purposes.

According to Cognitive Market Research, the global Data Preparation Tools market size will be USD XX million in 2025. It will expand at a compound annual growth rate (CAGR) of XX% from 2025 to 2031.

North America held the major market share for more than XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031. Europe accounted for a market share of over XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031. Asia Pacific held a market share of around XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031. Latin America had a market share of more than XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031. Middle East and Africa had a market share of around XX% of the global revenue and was estimated at a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031. KEY DRIVERS

Increasing Volume of Data and Growing Adoption of Business Intelligence (BI) and Analytics Driving the Data Preparation Tools Market

As organizations grow more data-driven, the integration of data preparation tools with Business Intelligence (BI) and advanced analytics platforms is becoming a critical driver of market growth. Clean, well-structured data is the foundation for accurate analysis, predictive modeling, and data visualization. Without proper preparation, even the most advanced BI tools may deliver misleading or incomplete insights. Businesses are now realizing that to fully capitalize on the capabilities of BI solutions such as Power BI, Qlik, or Looker, their data must first be meticulously prepared. Data preparation tools bridge this gap by transforming disparate raw data sources into harmonized, analysis-ready datasets. In the financial services sector, for example, firms use data preparation tools to consolidate customer financial records, transaction logs, and third-party market feeds to generate real-time risk assessments and portfolio analyses. The seamless integration of these tools with analytics platforms enhances organizational decision-making and contributes to the widespread adoption of such solutions. The integration of advanced technologies such as artificial intelligence (AI) and machine learning (ML) into data preparation tools has significantly improved their efficiency and functionality. These technologies automate complex tasks like anomaly detection, data profiling, semantic enrichment, and even the suggestion of optimal transformation paths based on patterns in historical data. AI-driven data preparation not only speeds up workflows but also reduces errors and human bias. In May 2022, Alteryx introduced AiDIN, a generative AI engine embedded into its analytics cloud platform. This innovation allows users to automate insights generation and produce dynamic documentation of business processes, revolutionizing how businesses interpret and share data. Similarly, platforms like DataRobot integrate ML models into the data preparation stage to improve the quality of predictions and outcomes. These innovations are positioning data preparation tools as not just utilities but as integral components of the broader AI ecosystem, thereby driving further market expansion. Data preparation tools address these needs by offering robust solutions for data cleaning, transformation, and integration, enabling telecom and IT firms to derive real-time insights. For example, Bharti Airtel, one of India’s largest telecom providers, implemented AI-based data preparation tools to streamline customer data and automate insights generation, thereby improving customer support and reducing operational costs. As major market players continue to expand and evolve their services, the demand for advanced data analytics powered by efficient data preparation tools will only intensify, propelling market growth. The exponential growth in global data generation is another major catalyst for the rise in demand for data preparation tools. As organizations adopt digital technologies and connected devices proliferate, the volume of data produced has surged beyond what traditional tools can handle. This deluge of information necessitates modern solutions capable of preparing vast and complex datasets efficiently. According to a report by the Lin...

According to Cognitive Market Research, the global Business Intelligence market size is USD 16.9 million in 2023 and will expand at a compound annual growth rate (CAGR) of 9.50% from 2023 to 2030.

The demand for Business Intelligence s is rising due to the increasing data complexity and rising focus on data-driven decision-making.
Demand for adults remains higher in the Business Intelligence market.
The Business intelligence platform category held the highest Business intelligence market revenue share in 2023.
North American Business Intelligence will continue to lead, whereas the Asia-Pacific Business Intelligence market will experience the most substantial growth until 2030.

Growing Emphasis on Data-Driven Decision-Making to Provide Viable Market Output

In the Business Intelligence Tools market, the increasing recognition of the strategic importance of data-driven decision-making serves as a primary driver. Organizations across various industries are realizing the transformative power of insights derived from BI tools. As the volume of data generated continues to soar, businesses seek sophisticated tools that can efficiently analyze and interpret this information. The ability of BI tools to convert raw data into actionable insights empowers decision-makers to formulate informed strategies, enhance operational efficiency, and gain a competitive edge in a data-centric business landscape.

In June 2020, SAS and Microsoft established a comprehensive technology and go-to-market strategic alliance. As part of the collaboration, SAS's industry solutions and analytical products will be moved to Microsoft Azure, SAS Cloud's preferred cloud provider.

Source-news.microsoft.com/2020/06/15/sas-and-microsoft-partner-to-further-shape-the-future-of-analytics-and-ai/#:~:text=and%20SAS%20today%20announced%20an,from%20their%20digital%20transformation%20initiatives.

Rise in Adoption of Advanced Analytics and Artificial Intelligence to Propel Market Growth

Another significant driver in the Business Intelligence Tools market is the escalating adoption of advanced analytics and artificial intelligence (AI) capabilities. Modern BI tools are incorporating AI-driven functionalities such as machine learning algorithms, natural language processing, and predictive analytics. These technologies enable users to uncover deeper insights, identify patterns, and predict future trends. The integration of AI not only enhances the analytical capabilities of BI tools but also automates processes, reducing manual efforts and improving the overall efficiency of data analysis. This trend aligns with the industry's pursuit of more intelligent and automated BI solutions to derive maximum value from data assets.

In March 2020, IBM created a new, dynamic global dashboard to display the global spread of COVID-19 with the assistance of IBM Cognos Analytics. The World Health Organization (WHO) and state and municipal governments provide the COVID-19 data displayed in this dashboard.

Source-www.ibm.com/blog/creating-trusted-covid-19-data-for-communities/

Market Dynamics of the Business Intelligence tool Market

Key Drivers for Business Intelligence tool Market

Increasing Demand for Data-Driven Decision Making Across Various Sectors: As companies produce vast amounts of data, there is an escalating requirement for tools that can analyze and convert raw data into actionable insights. Business Intelligence (BI) tools facilitate quicker and more precise strategic decisions in areas such as sales, finance, operations, and customer service.

Transition to Cloud-Based BI Solutions for Enhanced Scalability and Accessibility: Organizations are progressively shifting from on-premise BI systems to cloud-based solutions, which provide real-time access, foster collaboration, and reduce infrastructure expenses. This transition enhances scalability and accommodates hybrid or remote work settings.

Incorporation of AI and Machine Learning for Enhanced Predictive Analytics: Sophisticated BI tools are incorporating artificial intelligence and machine learning technologies to deliver predictive forecasting, anomaly detection, and natural language querying—thereby improving the accuracy of business forecasts and enhancing user accessibility.

Key Restraints for Business Intelligence tool Market

High Initial Setup and Customization Costs for SMEs: Small and medium-sized...

The HR analytics tools market is experiencing robust growth, driven by the increasing need for data-driven decision-making in human resource management. The market, estimated at $15 billion in 2025, is projected to achieve a compound annual growth rate (CAGR) of 12% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. Firstly, organizations are increasingly leveraging data to optimize recruitment processes, improve employee engagement, and enhance workforce planning. Secondly, advancements in artificial intelligence (AI) and machine learning (ML) are enabling more sophisticated analytics capabilities, providing actionable insights into employee behavior, performance, and attrition. Thirdly, the rising adoption of cloud-based HR solutions is facilitating easier access to data and enhanced collaboration across HR teams. The market is segmented by various tools, including Python, RStudio, Tableau, KNIME, Power BI, Microsoft Excel, Orange, and Apache Hadoop, each catering to different analytical needs and organizational scale. Despite the significant growth potential, the market faces certain challenges. Data privacy and security concerns remain a major hurdle, especially given the sensitive nature of employee data. The lack of skilled professionals proficient in data analytics and HR practices also presents a limitation. Furthermore, the integration of disparate HR data sources can be complex and time-consuming. However, these challenges are being addressed through the development of robust data security protocols, specialized training programs, and integrated HR software solutions. The North American region currently holds the largest market share, but Asia-Pacific is anticipated to show the fastest growth in the coming years due to the increasing adoption of HR analytics tools in rapidly growing economies.

The Data Visualization Tools Market size was valued at USD 10.39 billion in 2023 and is projected to reach USD 22.12 billion by 2032, exhibiting a CAGR of 11.4 % during the forecasts period. This unprecedented growth is attributed to the increasing demand for real-time data analysis, the need for effective decision-making, and the rising adoption of cloud-based data visualization tools. Additionally, government initiatives aimed at improving data literacy and the implementation of data visualization solutions in various industry verticals are further fueling market growth. Data visualization tools enable businesses and individuals to transform complex data into insightful visual representations. Tools like Tableau, Power BI, and Google Data Studio offer user-friendly interfaces to create interactive charts, graphs, and dashboards. They help analyze trends, patterns, and correlations, aiding decision-making processes. Advanced features include real-time data updates, collaboration capabilities, and integration with various data sources like databases and cloud services.

Explore the booming Data Visualization market! Discover key insights, growth drivers, market size estimations, and CAGR trends for 2025-2033. Understand applications, types, and leading companies in this essential business intelligence sector.

The Data Lens (Visualizations of Data) market is experiencing robust growth, driven by the increasing need for businesses to derive actionable insights from complex datasets. The market, currently estimated at $50 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This growth is fueled by several key factors, including the rising adoption of cloud-based analytics platforms, the proliferation of big data, and the growing demand for data-driven decision-making across diverse industries. Businesses are increasingly recognizing the importance of visualizing data to identify trends, patterns, and anomalies, leading to improved operational efficiency, enhanced strategic planning, and better customer understanding. The market is segmented by various software solutions, including business intelligence platforms (like Tableau, Sisense, and Qlikview), data visualization tools (such as Plotly and Chartio), and specialized analytics platforms from vendors like Alteryx and IBM. The competitive landscape is dynamic, with established players and innovative startups vying for market share through continuous product development and strategic partnerships. The continued expansion of the Data Lens market is expected to be further propelled by advancements in artificial intelligence (AI) and machine learning (ML), which are enhancing the capabilities of data visualization tools. AI-powered features such as automated insights generation and predictive analytics are transforming how businesses interact with and interpret their data. Geographic expansion, particularly in emerging economies, is another significant growth driver. However, challenges remain, including the need for skilled data analysts to effectively utilize these tools and the complexity associated with integrating diverse data sources. Nevertheless, the overall outlook for the Data Lens market remains highly positive, indicating a sustained period of substantial growth and innovation throughout the forecast period.

Description

This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

Key Features

• Country: Name of the country.
• Density (P/Km2): Population density measured in persons per square kilometer.
• Abbreviation: Abbreviation or code representing the country.
• Agricultural Land (%): Percentage of land area used for agricultural purposes.
• Land Area (Km2): Total land area of the country in square kilometers.
• Armed Forces Size: Size of the armed forces in the country.
• Birth Rate: Number of births per 1,000 population per year.
• Calling Code: International calling code for the country.
• Capital/Major City: Name of the capital or major city.
• CO2 Emissions: Carbon dioxide emissions in tons.
• CPI: Consumer Price Index, a measure of inflation and purchasing power.
• CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
• Currency_Code: Currency code used in the country.
• Fertility Rate: Average number of children born to a woman during her lifetime.
• Forested Area (%): Percentage of land area covered by forests.
• Gasoline_Price: Price of gasoline per liter in local currency.
• GDP: Gross Domestic Product, the total value of goods and services produced in the country.
• Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
• Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
• Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
• Largest City: Name of the country's largest city.
• Life Expectancy: Average number of years a newborn is expected to live.
• Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
• Minimum Wage: Minimum wage level in local currency.
• Official Language: Official language(s) spoken in the country.
• Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
• Physicians per Thousand: Number of physicians per thousand people.
• Population: Total population of the country.
• Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
• Tax Revenue (%): Tax revenue as a percentage of GDP.
• Total Tax Rate: Overall tax burden as a percentage of commercial profits.
• Unemployment Rate: Percentage of the labor force that is unemployed.
• Urban Population: Percentage of the population living in urban areas.
• Latitude: Latitude coordinate of the country's location.
• Longitude: Longitude coordinate of the country's location.

Potential Use Cases

• Analyze population density and land area to study spatial distribution patterns.
• Investigate the relationship between agricultural land and food security.
• Examine carbon dioxide emissions and their impact on climate change.
• Explore correlations between economic indicators such as GDP and various socio-economic factors.
• Investigate educational enrollment rates and their implications for human capital development.
• Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
• Study labor market dynamics through indicators such as labor force participation and unemployment rates.
• Investigate the role of taxation and its impact on economic development.
• Explore urbanization trends and their social and environmental consequences.

Data Source: This dataset was compiled from multiple data sources

If this was helpful, a vote is appreciated ❤️ Thank you 🙂

Context

This dataset was curated from the Bing search logs (desktop users only) over the period of Jan 1st, 2020 – (Current Month - 1). Only searches that were issued many times by multiple users were included. Dataset includes queries from all over the world that had an intent related to the Coronavirus or Covid-19. In some cases this intent is explicit in the query itself, e.g. “Coronavirus updates Seattle” in other cases it is implicit , e.g. “Shelter in place”. Implicit intent of search queries (e.g. Toilet paper) were extracted by using Random walks on the click graph approach as outlined in the following paper by Nick Craswell et al at Microsoft Research: https://www.microsoft.com/en-us/research/wp-content/uploads/2007/07/craswellszummer-random-walks-sigir07.pdf All personal data was removed. Source - https://msropendata.com/datasets/c5031874-835c-48ed-8b6d-31de2dad0654

Acknowledgements

Data Source: Bing Coronavirus Query set (https://github.com/microsoft/BingCoronavirusQuerySet)

License - Open Use of Data Agreement v1.0

Content

Inside the data folder there is a folder 2020 (for the year) which contains two kinds of files.

QueriesByCountry_DateRange.tsv : A tab separated text file that contains queries with Coronavirus intent by Country. QueriesByState_DateRange.tsv : A tab separated text file that contains queries with Coronavirus intent by State.

QueriesByCountry Date : string, Date on which the query was issued.

Query : string, The actual search query issued by user(s).

IsImplicitIntent : bool, True if query did not mention covid or coronavirus or sarsncov2 (e.g, “Shelter in place”). False otherwise.

Country : string, Country from where the query was issued.

PopularityScore : int, Value between 1 and 100 inclusive. 1 indicates least popular query on the day/Country with Coronavirus intent, and 100 indicates the most popular query for the same Country on the same day.

QueriesByState Date : string, Date on which the query was issued.

Query : string, The actual search query issued by user(s).

IsImplicitIntent : bool, True if query did not mention covid or coronavirus or sarsncov2 (e.g, “Shelter in place”). False otherwise.

State : string, State from where the query was issued.

Country :string, Country from where the query was issued.

PopularityScore : int, Value between 1 and 100 inclusive. 1 indicates least popular query on the day/State/Country with Coronavirus intent, and 100 indicates the most popular query for the same geogrpahy on the same day.

The Data Virtualization Cloud market is experiencing steady growth, projected to reach $1929.1 million in 2025, exhibiting a Compound Annual Growth Rate (CAGR) of 2.3%. This growth is fueled by several key factors. The increasing need for real-time data access and integration across diverse data sources is driving demand. Organizations are seeking efficient and cost-effective solutions to manage and analyze their exponentially growing data volumes, leading to the adoption of cloud-based data virtualization platforms. The rise of hybrid cloud environments further accelerates this trend, as businesses need seamless data access across on-premises and cloud-based systems. Furthermore, the increasing adoption of advanced analytics and business intelligence tools necessitates robust data virtualization capabilities to provide a unified and consistent view of data. Competitive pressures also push businesses to improve operational efficiency and agility, with data virtualization playing a crucial role in achieving these goals. Major market players like Denodo, Microsoft, Google, Alibaba, IBM, Informatica, Oracle, SAP, Tibco, Datometry, and VMware are actively contributing to market expansion through continuous innovation and strategic partnerships. However, challenges remain, including complexities in data governance and security, the need for skilled professionals to implement and manage these solutions, and potential integration challenges with legacy systems. Despite these obstacles, the long-term outlook for the Data Virtualization Cloud market remains positive, driven by ongoing technological advancements and increasing enterprise adoption. The market is expected to experience consistent growth throughout the forecast period (2025-2033), driven by factors such as the increasing volume and variety of data, the need for improved data accessibility, and the rise of cloud computing.