As of February 2025, it was found that men between the ages of 25 and 34 years made up Facebook's largest audience, accounting for 18.5 percent of global users. Additionally, Facebook's second-largest audience base could be found with men aged 18 to 24 years. Facebook connects the world Founded in 2004 and going public in 2012, Facebook is one of the biggest internet companies in the world with influence that goes beyond social media. It is widely considered as one of the Big Four tech companies, along with Google, Apple, and Amazon (all together known under the acronym GAFA). Facebook is the most popular social network worldwide and the company also owns three other billion-user properties: mobile messaging apps WhatsApp and Facebook Messenger, as well as photo-sharing app Instagram. Facebook usersThe vast majority of Facebook users connect to the social network via mobile devices. This is unsurprising, as Facebook has many users in mobile-first online markets. Currently, India ranks first in terms of Facebook audience size with 378 million users. The United States, Brazil, and Indonesia also all have more than 100 million Facebook users each.

The Location-Based Analytics market is experiencing robust growth, driven by the increasing adoption of mobile devices, the proliferation of location data from various sources (GPS, Wi-Fi, cellular networks), and the rising need for businesses to understand and leverage customer location insights for improved decision-making. A compound annual growth rate (CAGR) of, let's assume, 15% from 2025 to 2033 indicates a significant expansion of the market, with a projected market size of approximately $80 billion by 2033 (assuming a 2025 market size of $25 billion, a reasonable estimate given the presence of major players like Google and IBM). Key market drivers include the need for enhanced customer experience personalization, precise supply chain optimization, real-time risk management, and improved marketing campaign effectiveness. The increasing availability of sophisticated analytical tools and platforms is further fueling this growth. However, challenges such as data privacy concerns, the complexity of integrating diverse data sources, and the need for skilled professionals to manage and interpret location data act as restraints to some extent. Market segmentation reveals a diverse landscape, with solutions catering to various industries (retail, logistics, healthcare, etc.). Companies like Alteryx, Google, HERE Technologies, Hexagon, Microsoft, Oracle, Pitney Bowes, Sisense, Syncsort, IBM, and Quppa are actively competing in this space, each offering unique technologies and capabilities. Regional market variations exist, with North America and Europe currently holding significant shares, but developing economies in Asia-Pacific and Latin America are showing rapid growth potential, indicating the market's global reach and future expansion. The ongoing integration of location data with other data sources (e.g., demographic, transactional) is driving the emergence of more comprehensive and powerful analytical solutions, leading to further innovation and market expansion within the forecast period.

This dataset is the result of cleaning and aggregating data as part of the Process and Analyze phases of the Google Data Analytics Capstone Project Cyclistic Case Study 2013-2021 with demographics. The original data for the project has been made available by Motivate International Inc. under this license.

The Healthcare Descriptive Analytics Market is experiencing robust growth, projected to reach $18.36 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 23.50% from 2025 to 2033. This expansion is driven by several key factors. The increasing adoption of electronic health records (EHRs) generates massive datasets ripe for analysis, leading to improved patient care, operational efficiency, and more effective research. Furthermore, advancements in big data technologies and artificial intelligence (AI) are enabling sophisticated analytical capabilities, allowing healthcare providers and organizations to extract valuable insights from complex healthcare data. The demand for data-driven decision-making in areas like precision medicine, population health management, and risk stratification is further fueling market growth. Strong government initiatives promoting healthcare data interoperability and the rising need for improved healthcare outcomes also contribute significantly to the market's expansion. Market segmentation reveals strong performance across various applications. Clinical data analytics, focused on improving diagnoses and treatment, holds a significant share, followed by financial data analytics used for optimizing revenue cycle management and reducing costs. The software component dominates the market due to its versatility and scalability, complemented by robust growth in cloud-based deployment models, owing to their cost-effectiveness, accessibility, and enhanced security features. Private organizations, especially hospitals and clinics, are leading end-users, driving adoption across various segments. Geographically, North America is currently the largest market, fueled by advanced healthcare infrastructure and early adoption of analytical technologies. However, the Asia-Pacific region is poised for substantial growth, driven by increasing healthcare spending and technological advancements. The competitive landscape is dynamic, with established players like IBM, Oracle, and McKesson alongside specialized healthcare analytics firms, all vying for market share through innovative solutions and strategic partnerships. Recent developments include: In November 2022, Ursa Health updated Ursa Studio, its healthcare analytics development platform, to help organizations meet the requirements of the Centers for Medicare and Medicaid Services (CMS)., In November 2022, Hartford HealthCare entered a long-term partnership with Google Cloud to advance the healthcare digital transformation, improve data analytics, and enhance care delivery and access.. Key drivers for this market are: Need for Comprehensive Analytics, Integration of Big Data into Healthcare. Potential restraints include: Need for Comprehensive Analytics, Integration of Big Data into Healthcare. Notable trends are: Cloud-based Segment Expected to Hold a Significant Share of the Market During the Forecast Period.

The Dataflix COVID dataset is a centralized repository of up-to-date and curated data focused on key tracking metics and U.S. census data. The dataset is publicly-readable & accessible on Google BigQuery – ready for analysis, analytics and machine learning initiatives. The dataset is built on data sourced from trusted sources like CSSE at Johns Hopkins University and government agencies, covering a wide range of metrics including confirmed cases, new cases, % population, mortality rate and deaths, aggregated at various geographic levels including city, county, state and country. New data is published on daily basis. Our objective is to make structured COVID data available for organizations and individuals to help in the fight against COVID-19. Example, health authorities will be able to build reports & dashboards to efficiently deploy vital resources like hospital beds and ventilators as they track the spread of the disease. Or epidemiologists can use the dataset to complement their existing models & datasets, and generate better forecasts of hotspots and trends. Learn more

The Dataflix COVID dataset is a centralized repository of up-to-date and curated data focused on key tracking metics and U.S. census data. The dataset is publicly-readable & accessible on Google BigQuery – ready for analysis, analytics and machine learning initiatives. The dataset is built on data sourced from trusted sources like CSSE at Johns Hopkins University and government agencies, covering a wide range of metrics including confirmed cases, new cases, % population, mortality rate and deaths, aggregated at various geographic levels including city, county, state and country. New data is published on daily basis. Our objective is to make structured COVID data available for organizations and individuals to help in the fight against COVID-19. Example, health authorities will be able to build reports & dashboards to efficiently deploy vital resources like hospital beds and ventilators as they track the spread of the disease. Or epidemiologists can use the dataset to complement their existing models & datasets, and generate better forecasts of hotspots and trends. 瞭解詳情

The Dataflix COVID dataset is a centralized repository of up-to-date and curated data focused on key tracking metics and U.S. census data. The dataset is publicly-readable & accessible on Google BigQuery – ready for analysis, analytics and machine learning initiatives. The dataset is built on data sourced from trusted sources like CSSE at Johns Hopkins University and government agencies, covering a wide range of metrics including confirmed cases, new cases, % population, mortality rate and deaths, aggregated at various geographic levels including city, county, state and country. New data is published on daily basis. Our objective is to make structured COVID data available for organizations and individuals to help in the fight against COVID-19. Example, health authorities will be able to build reports & dashboards to efficiently deploy vital resources like hospital beds and ventilators as they track the spread of the disease. Or epidemiologists can use the dataset to complement their existing models & datasets, and generate better forecasts of hotspots and trends. Más información

The Dataflix COVID dataset is a centralized repository of up-to-date and curated data focused on key tracking metics and U.S. census data. The dataset is publicly-readable & accessible on Google BigQuery – ready for analysis, analytics and machine learning initiatives. The dataset is built on data sourced from trusted sources like CSSE at Johns Hopkins University and government agencies, covering a wide range of metrics including confirmed cases, new cases, % population, mortality rate and deaths, aggregated at various geographic levels including city, county, state and country. New data is published on daily basis. Our objective is to make structured COVID data available for organizations and individuals to help in the fight against COVID-19. Example, health authorities will be able to build reports & dashboards to efficiently deploy vital resources like hospital beds and ventilators as they track the spread of the disease. Or epidemiologists can use the dataset to complement their existing models & datasets, and generate better forecasts of hotspots and trends. Saiba mais

The Dataflix COVID dataset is a centralized repository of up-to-date and curated data focused on key tracking metics and U.S. census data. The dataset is publicly-readable & accessible on Google BigQuery – ready for analysis, analytics and machine learning initiatives. The dataset is built on data sourced from trusted sources like CSSE at Johns Hopkins University and government agencies, covering a wide range of metrics including confirmed cases, new cases, % population, mortality rate and deaths, aggregated at various geographic levels including city, county, state and country. New data is published on daily basis. Our objective is to make structured COVID data available for organizations and individuals to help in the fight against COVID-19. Example, health authorities will be able to build reports & dashboards to efficiently deploy vital resources like hospital beds and ventilators as they track the spread of the disease. Or epidemiologists can use the dataset to complement their existing models & datasets, and generate better forecasts of hotspots and trends. Weitere Informationen