The All CMS Data Feeds dataset is an expansive resource offering access to 119 unique report feeds, providing in-depth insights into various aspects of the U.S. healthcare system including nursing facility owners and accountable care organization participants contact data. With over 25.8 billion rows of data meticulously collected since 2007, this dataset is invaluable for healthcare professionals, analysts, researchers, and businesses seeking to understand and analyze healthcare trends, performance metrics, and demographic shifts over time. The dataset is updated monthly, ensuring that users always have access to the most current and relevant data available.

Dataset Overview:

118 Report Feeds: - The dataset includes a wide array of report feeds, each providing unique insights into different dimensions of healthcare. These topics range from Medicare and Medicaid service metrics, patient demographics, provider information, financial data, and much more. The breadth of information ensures that users can find relevant data for nearly any healthcare-related analysis. - As CMS releases new report feeds, they are automatically added to this dataset, keeping it current and expanding its utility for users.

25.8 Billion Rows of Data:

• With over 25.8 billion rows of data, this dataset provides a comprehensive view of the U.S. healthcare system. This extensive volume of data allows for granular analysis, enabling users to uncover insights that might be missed in smaller datasets. The data is also meticulously cleaned and aligned, ensuring accuracy and ease of use.

Historical Data Since 2007: - The dataset spans from 2007 to the present, offering a rich historical perspective that is essential for tracking long-term trends and changes in healthcare delivery, policy impacts, and patient outcomes. This historical data is particularly valuable for conducting longitudinal studies and evaluating the effects of various healthcare interventions over time.

Monthly Updates:

• To ensure that users have access to the most current information, the dataset is updated monthly. These updates include new reports as well as revisions to existing data, making the dataset a continuously evolving resource that stays relevant and accurate.

Data Sourced from CMS:

• The data in this dataset is sourced directly from the Centers for Medicare & Medicaid Services (CMS). After collection, the data is meticulously cleaned and its attributes are aligned, ensuring consistency, accuracy, and ease of use for any application. Furthermore, any new updates or releases from CMS are automatically integrated into the dataset, keeping it comprehensive and current.

Use Cases:

Market Analysis:

• The dataset is ideal for market analysts who need to understand the dynamics of the healthcare industry. The extensive historical data allows for detailed segmentation and analysis, helping users identify trends, market shifts, and growth opportunities. The comprehensive nature of the data enables users to perform in-depth analyses of specific market segments, making it a valuable tool for strategic decision-making.

Healthcare Research:

• Researchers will find the All CMS Data Feeds dataset to be a robust foundation for academic and commercial research. The historical data, combined with the breadth of coverage across various healthcare metrics, supports rigorous, in-depth analysis. Researchers can explore the effects of healthcare policies, study patient outcomes, analyze provider performance, and more, all within a single, comprehensive dataset.

Performance Tracking:

• Healthcare providers and organizations can use the dataset to track performance metrics over time. By comparing data across different periods, organizations can identify areas for improvement, monitor the effectiveness of initiatives, and ensure compliance with regulatory standards. The dataset provides the detailed, reliable data needed to track and analyze key performance indicators.

Compliance and Regulatory Reporting:

• The dataset is also an essential tool for compliance officers and those involved in regulatory reporting. With detailed data on provider performance, patient outcomes, and healthcare utilization, the dataset helps organizations meet regulatory requirements, prepare for audits, and ensure adherence to best practices. The accuracy and comprehensiveness of the data make it a trusted resource for regulatory compliance.

Data Quality and Reliability:

The All CMS Data Feeds dataset is designed with a strong emphasis on data quality and reliability. Each row of data is meticulously cleaned and aligned, ensuring that it is both accurate and consistent. This attention to detail makes the dataset a trusted resource for high-stakes applications, where data quality is critical.

Integration and Usability:

Ease of Integration:

• The dataset is provided in a CSV format, which is widely compatible with most data analysis too...

Financial data service providers offer financial market data and related services, primarily real-time feeds, portfolio analytics, research, pricing and valuation data, to financial institutions, traders and investors. Companies aggregate data and content from stock exchange feeds, broker and dealer desks and regulatory filings to distribute financial news and business information to the investment community. Recent globalization of the world capital market has benefited the financial sector and increased trading speed. Businesses rely on real-time data more than ever to help them make informed decisions. When considering a data service provider, an easy-to-use interface that shows customized, relevant information is vital for clients. During times of economic uncertainty, this information becomes more crucial than ever. Clients want information as soon and as frequently as possible, causing providers to prioritize efficiency and delivery. This was evident during the pandemic, the high interest rate environment in the latter part of the period and as the Fed cuts rates in 2024. Increased automation has helped industry players process large volumes of financial data, reducing analysis and reporting times. In addition, automation has reduced operational costs and reduced human data errors. These trends have resulted in growing revenue, which has risen at a CAGR of 3.2% to $21.9 billion over the past five years, including a 3.5% uptick in 2024 alone. Corporate profit will continue to expand as inflationary concerns begin to wane slowly. This will lead many companies to take on new clients as financial data helps them gain insight into operating their business amid ongoing trends and economic shakeups. With technology constantly advancing, service providers will continue investing in research and development to improve their products and services and best serve their clients. As technological advances continue, smaller players will be able to better compete with larger industry players. While this may lead to new companies joining the industry, larger providers will resume consolidation activity to expand their customer base. Overall, revenue is expected to swell at a CAGR of 2.7% to $25.0 billion by the end of 2029.

Data Broker Market is Segmented by Data Type (Consumer Data, Business Data, and More), End User (Marketing and Advertising Agencies, Financial Services and Insurance, and More), Data Acquisition Channel (Online Tracking and Cookies, Mobile Apps and SDKs, and More), Delivery Mode (APIs and Data Feeds, Cloud-Based Marketplaces, and More), and by Geography. The Market Forecasts are Provided in Terms of Value (USD).

The Feed Grains Database contains statistics on four feed grains (corn, grain sorghum, barley, and oats), foreign coarse grains (feed grains plus rye, millet, and mixed grains), hay, and related items.

Financial Research Software Market size was valued at USD 1.23 Billion in 2024 and is projected to reach USD 1.82 Billion by 2031, growing at a CAGR of 3.5% during the forecast period 2024-2031.

Global Financial Research Software Market Drivers

Growing Demand for Data Analytics: Increasing demand for data-driven insights and analytics in the financial sector drives the adoption of financial research software to analyze market trends, investment opportunities, risk factors, and financial performance metrics.

Technological Advancements: Ongoing advancements in financial research software, including artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and big data analytics, enhance data processing capabilities, improve accuracy, and enable predictive modeling for investment decision-making.

Regulatory Compliance Requirements: Stringent regulatory requirements and compliance standards in the financial industry drive the adoption of financial research software to ensure regulatory compliance, risk management, and transparency in reporting and disclosure practices.

Investment Management and Portfolio Optimization: Financial research software enables investment professionals, portfolio managers, and asset allocators to conduct comprehensive research, perform quantitative analysis, and optimize investment portfolios to maximize returns and mitigate risks.

Rise of Robo-Advisors and Fintech Solutions: The rise of robo-advisors, digital wealth management platforms, and fintech solutions drives demand for financial research software with automated investment algorithms, portfolio rebalancing tools, and personalized financial advice for retail investors and wealth management clients.

Globalization and Market Integration: Globalization of financial markets and increased market integration drive the need for financial research software that provides real-time market data, news feeds, and economic indicators to support informed decision-making in a dynamic and interconnected marketplace.

Shift Towards ESG Investing: The growing focus on environmental, social, and governance (ESG) factors in investment decision-making drives demand for financial research software with ESG data integration, sustainability metrics, and impact analysis tools to support responsible investing strategies.

Risk Management and Stress Testing: Financial research software enables financial institutions and investment firms to conduct risk assessments, scenario analysis, and stress testing to evaluate portfolio resilience, liquidity risk, credit risk, and market volatility in various market conditions.

Alternative Data Sources and Quantitative Analysis: Financial research software integrates alternative data sources, such as social media sentiment, satellite imagery, and consumer behavior data, into quantitative models and analytical frameworks to gain insights into market trends and investment opportunities.

Demand for Customization and Integration: Financial institutions and investment professionals seek customizable financial research software solutions that can be tailored to their specific needs, integrated with existing systems and workflows, and scalable to accommodate future growth and expansion.

According to Cognitive Market Research, the global Financial Data Service market size will be USD 24152.5 million in 2024. It will expand at a compound annual growth rate (CAGR) of 8.50% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 9661.00 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.7% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 7245.75 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 5555.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.5% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 1207.63 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.9% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 483.05 million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.2% from 2024 to 2031.
Datafeed/API solutions are the dominant segment, as they allow seamless data integration into existing systems and platforms, making them ideal for companies requiring real-time data across multiple applications

Market Dynamics of Financial Data Service Market

Key Drivers for Financial Data Service Market

Increased Data-Driven Decision-Making to Boost Market Growth

As digital transformation sweeps through financial services, data-driven decision-making has become essential for businesses to remain competitive. Institutions, both financial and non-financial, are increasingly leveraging financial data to guide strategic investments, manage risks, and streamline operations. By utilizing real-time data and predictive analytics, companies gain actionable insights to optimize their investment portfolios and financial planning. With the enhanced capability to analyze data trends and assess market scenarios, businesses can mitigate risks more effectively, making this driver critical to the growth of the financial data service market. For instance, in September 2022, Alibaba Cloud, the digital technology and intellectual backbone of Alibaba Group, launched a comprehensive suite of Alibaba Cloud for Financial Services solutions. Comprising over 70 products, these solutions are designed to help financial services institutions of all sizes across banking, FinTech, insurance, and securities, digitalize their operations

Advancements in Analytics Technology to Drive Market Growth

The integration of advanced analytics technologies like artificial intelligence (AI) and machine learning (ML) in financial data services has significantly enhanced the accuracy and scope of market insights. AI and ML enable companies to process vast amounts of financial data, identify patterns, and make predictions, thus facilitating strategic planning and investment optimization. These technologies also allow for real-time insights, giving firms a competitive advantage in rapidly evolving markets. With continuous improvements in AI and ML, the demand for advanced data services is expected to grow, positioning this as a key driver of market expansion.

Restraint Factor for the Financial Data Service Market

High Cost of Data Services Will Limit Market Growth

The high cost of premium financial data services is a significant restraint, particularly for small and medium-sized enterprises (SMEs). Many advanced platforms and data feeds come with substantial subscription fees, limiting their accessibility to larger organizations with more considerable budgets. This cost barrier restricts smaller firms from fully integrating advanced data insights into their operations. As a result, high subscription costs prevent widespread adoption among SMEs, hindering the financial data service market’s overall growth potential.

Trends for the Financial Data Service Market

Blockchain-based Data Services as an opportunity for the market

Blockchain-based data services offer a secure, transparent, and decentralized approach to financial data management. By leveraging blockchain technology, finance data services can provide tamper-proof and auditable data storage, ensuring the integrity and accuracy of financial data. This can help...

View LSEG's Lipper Fund Research Database, providing independent fund content to benchmark fund performance, manage risk, and more.

Comprehensive dataset of 3 Pet food and animal feeds in Iran as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

In 2012, the Feed the Future Innovation Lab for Nutrition initiated a program of research in Nepal called the PoSHAN surveys. Funded by the United States Agency for International Development (USAID), the PoSHAN surveys were designed and implemented as an annual assessment of community, household, individual conditions. The aim was to determine a) the links among agriculture, nutrition, health, and b) how exposure to a range of policy and program interventions may influence household food security, poverty, and the diets, health and nutrition of young children and their mothers. The datasets uploaded here consists of four national surveys collected from 2013-2016 in Nepal and additional seasonal surveys. The full study design is described in detail in this manuscript: http://pubs.sciepub.com/jfs/6/2/5/index.html The data archive can be found here: https://archive.data.jhu.edu/dataverse/PoSHAN_Surveys

CFA provides data feeds for Incidents, Total Fire Bans & Fire Danger Ratings and latest news.\r \r To receive CFA RSS feeds you need a feed reader and must also subscribe to CFA feeds.\r \r To subscribe to one of the CFA RSS feeds:\r \r Click on the RSS button next to the feed you want (or ctrl, click for Mac users).\r Copy the URL of the page that is displayed.\r Paste the address in the appropriate place in your feed reader.\r Important Note: Some third party readers will not refresh as frequently as is required for live updates. It is recommended that if your reader cannot be set to update at least every 5 minutes that you check the respective web pages (Incidents and Total Fire Bans & Fire Danger Ratings) for the most up to date version.\r \r These RSS feeds conforms to RSS 2.0 specification and update every minute.

This is a data schema created using Agri-food Data Canada's Semantic Engine . Data schemas describe data that are collected on an ongoing basis from research centres, and provide add-on documentation that enhances the value of raw data. This schema is used to collect and organize data from reports of feed analysis from all samples, including information about diets and ingredients. Analysis is done by A&L Lab Canada. Data described in this schema is sample data, to request access to the related data, please visit the Ontario Beef Research Centre Data Portal. Note: variables "company_name" and "customer_n" are excluded from the sample data file as these contain sensitive information.

The Fish Meal for Feed market is an essential component of the global aquaculture and livestock industries, serving as a high-protein ingredient in animal feed formulations. This market has experienced significant growth over the years due to the increasing demand for quality protein sources in animal nutrition, par

The feed industry plays a crucial role in providing nutrition to livestock and poultry, which in turn helps in ensuring food security for humans. Learn about the different types of animal feed, the sourcing and processing of raw materials, and the importance of high-quality feed in animal health and welfare. Discover how the feed industry is evolving to meet the increasing nutritional needs of animals and contributing to overall food security.

The Carotenoid Feed Additives market has emerged as a vital sector within the global agricultural and animal husbandry industries, driven by the increasing demand for high-quality animal products. Carotenoid additives, which are naturally occurring pigments found in various plants, provide essential health benefits

The Concentrated Feeds market, an essential segment of the animal nutrition industry, has gained significant prominence in recent years due to the rising demand for livestock products and the need for efficient feeding practices. Concentrated feeds, which are high in nutrients and designed to complement roughage fee

The Dog Food Data Extracted from Chewy (USA) dataset contains 4,500 detailed records of dog food products sourced from one of the leading pet supply platforms in the United States, Chewy. This dataset is ideal for businesses, researchers, and data analysts who want to explore and analyze the dog food market, including product offerings, pricing strategies, brand diversity, and customer preferences within the USA.

The dataset includes essential information such as product names, brands, prices, ingredient details, product descriptions, weight options, and availability. Organized in a CSV format for easy integration into analytics tools, this dataset provides valuable insights for those looking to study the pet food market, develop marketing strategies, or train machine learning models.

Key Features:

• Record Count: 4,500 dog food product records.
• Data Fields: Product names, brands, prices, descriptions, ingredients .. etc. Find more fields under data points section.
• Format: CSV, easy to import into databases and data analysis tools.
• Source: Extracted from Chewy’s official USA platform.
• Geography: Focused on the USA dog food market.

Use Cases:

• Market Research: Analyze trends and preferences in the USA dog food market, including popular brands, price ranges, and product availability.
• E-commerce Analysis: Understand how Chewy presents and prices dog food products, helping businesses compare their own product offerings.
• Competitor Analysis: Compare different brands and products to develop competitive strategies for dog food businesses.
• Machine Learning Models: Use the dataset for machine learning tasks such as product recommendation systems, demand forecasting, and price optimization.

The COKI Open Access Dataset measures open access performance for 142 countries and 5117 institutions and is available in JSON Lines format. The data is visualised at the COKI Open Access Dashboard: https://open.coki.ac/. The COKI Open Access Dataset is created with the COKI Academic Observatory data collection pipeline, which fetches data about research publications from multiple sources, synthesises the datasets and creates the open access calculations for each country and institution. Each week a number of specialised research publication datasets are collected. The datasets that are used for the COKI Open Access Dataset release include Crossref Metadata, Microsoft Academic Graph, Unpaywall and the Research Organization Registry. After fetching the datasets, they are synthesised to produce aggregate time series statistics for each country and institution in the dataset. The aggregate timeseries statistics include publication count, open access status and citation count. See https://open.coki.ac/data/ for the dataset schema. A new version of the dataset is deposited every week. Code The COKI Academic Observatory data collection pipeline is used to create the dataset. The COKI OA Website Github project contains the code for the web app that visualises the dataset at open.coki.ac. It can be found on Zenodo here. License COKI Open Access Dataset © 2022 by Curtin University is licenced under CC BY 4.0. Attributions This work contains information from: Microsoft Academic Graph which is made available under the ODC Attribution Licence. Crossref Metadata via the Metadata Plus program. Bibliographic metadata is made available without copyright restriction and Crossref generated data under a CC0 licence. See metadata licence information for more details. Unpaywall. The Unpaywall Data Feed is used under license. Data is freely available from Unpaywall via the API, data dumps and as a data feed. Research Organization Registry which is made available under a CC0 licence. The Curtin Open Knowledge Initiative (COKI) is a strategic initiative of the Research Office at Curtin, the Faculty of Humanities, School of Media, Creative Arts and Social Inquiry and the Curtin Institute for Computation, with additional support from the Andrew W. Mellon Foundation and the Arcadia Fund, a charitable fund of Lisbet Rausing and Peter Baldwin.

Live air quality data updates from the Queensland Governments air monitoring network updated hourly and published in XML format. \r \r The data used to compile this air quality information comes directly from the department's air monitoring network and has only undergone a preliminary quality check. \r \r If there is no data measured for a parameter, or data could not be retrieved from the monitoring station at this hour, no data will be shown. \r \r Only data for the current hour is available through the live data feed.

The Pet Additive Premixed Feed market is a rapidly evolving segment of the pet care industry, crucial for ensuring the health and well-being of our beloved pets. As pet owners increasingly prioritize quality nutrition, premixed feeds enriched with essential additives are gaining popularity for their convenience and