We receive a large flux of several 1000 real-time ticks per second from multiple sources across over 2000 currency pairs. From this raw data, Olsen computes and publishes a fixing every second, which is a reasonably tradable median level Bid and Ask.

We are a neutral data provider and not a broker or trading platform. Our fixing is therefore used by many traders to check their broker prices and minimize execution risk.

Sports Data Low-Latency Feed Market Outlook

According to our latest research for 2024, the global sports data low-latency feed market size stands at USD 1.47 billion. The market is experiencing robust growth, propelled by the increasing demand for real-time data delivery across various sports-related applications. The market is set to expand at a CAGR of 18.2% during the forecast period, reaching an estimated USD 6.45 billion by 2033. This growth is primarily driven by the rapid adoption of digital transformation in the sports industry, the surge in sports betting activities, and the proliferation of live streaming and fantasy sports platforms. As per our latest research, the sports data low-latency feed market is positioned for significant evolution, with technological advancements and increasing integration of artificial intelligence playing pivotal roles in shaping the industry landscape.

A major growth factor for the sports data low-latency feed market is the escalating demand for instant access to accurate sports information. With the rise of live sports broadcasting and the surge in in-play betting, stakeholders across the sports ecosystem require ultra-fast data feeds to ensure timely and precise delivery of critical match events, player statistics, and video content. This demand is further amplified by the expectations of modern sports fans, who seek real-time engagement and interactive experiences through various digital platforms. The integration of advanced data analytics and machine learning algorithms has enabled providers to deliver highly reliable and actionable insights, thereby enhancing the value proposition for end-users such as broadcasters, betting companies, and sports leagues. Consequently, the ability to provide low-latency data feeds has become a key differentiator in the competitive sports data market.

The proliferation of sports betting and fantasy sports platforms globally has significantly contributed to the growth of the sports data low-latency feed market. These platforms rely heavily on real-time data to facilitate seamless user experiences, minimize the risk of arbitrage, and ensure regulatory compliance. The legalization of sports betting in several jurisdictions, particularly in North America and Europe, has led to a surge in demand for high-speed, accurate data feeds that support dynamic odds calculation and in-play wagering. Furthermore, the increasing popularity of fantasy sports leagues has created new avenues for data feed providers to deliver comprehensive player statistics, match updates, and video highlights, all in real time. As the competitive landscape intensifies, companies are investing in advanced infrastructure and partnerships to enhance their data delivery capabilities and expand their market presence.

Technological advancements in network infrastructure, such as the deployment of 5G and edge computing, have played a crucial role in driving the sports data low-latency feed market forward. These technologies enable faster data transmission, reduced latency, and improved reliability, which are essential for delivering real-time sports content to a global audience. The adoption of cloud-based solutions has further facilitated scalability and flexibility, allowing stakeholders to manage large volumes of data efficiently and cost-effectively. Moreover, the integration of video analytics and artificial intelligence has opened new possibilities for automated content generation, personalized recommendations, and enhanced fan engagement. As the industry continues to evolve, the convergence of these technologies is expected to unlock new growth opportunities and redefine the standards for real-time sports data delivery.

Regionally, North America dominates the sports data low-latency feed market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The strong presence of major sports leagues, advanced technological infrastructure, and the rapid adoption of sports betting and fantasy sports platforms have positioned North America as the leading market. Europe is also experiencing significant growth, driven by the increasing popularity of football and the expansion of regulated betting markets. Asia Pacific is emerging as a high-growth region, fueled by rising sports viewership, digital transformation initiatives, and the growing adoption of cloud-based solutions. Latin America and the Middle East & Africa are witnessing steady growth, supported by investments in sports infrastructure and increasing internet penetration. The regional outlook for the mar

Contains information on the power provider feeds. Data indicates the response code for the various feeds as well as the data created date. Limited historical record inventory. Designed for and consumed by the MEMA Power Outage web application.

View LSEG's ICE Data Pricing and Reference Data, and find real-time market data, time-sensitive pricing, and reference data for securities trading.

The goal for Payroll Data Feed is to securely acquire pay data for all Federal Civilian employees by leveraging existing data extraction processes to the extent possible.Depending on the source of pay related data, one provider may submit payroll data for many agencies. Payroll data submissions from providers to EHRI represent actual payroll records in a given pay period. When a payroll data provider makes major system changes, it is responsible for ensuring that data accuracy and completeness are maintained. The Office of Personnel Management should be notified when any major system changes are planned. Then, the Office of Personnel Management will decide whether the payroll data provider should submit test data or continue to submit publication data.

Quadrant provides Insightful, accurate, and reliable mobile location data.

Our privacy-first mobile location data unveils hidden patterns and opportunities, provides actionable insights, and fuels data-driven decision-making at the world's biggest companies.

These companies rely on our privacy-first Mobile Location and Points-of-Interest Data to unveil hidden patterns and opportunities, provide actionable insights, and fuel data-driven decision-making. They build better AI models, uncover business insights, and enable location-based services using our robust and reliable real-world data.

We conduct stringent evaluations on data providers to ensure authenticity and quality. Our proprietary algorithms detect, and cleanse corrupted and duplicated data points – allowing you to leverage our datasets rapidly with minimal processing or cleaning. During the ingestion process, our proprietary Data Filtering Algorithms remove events based on a number of both qualitative factors, as well as latency and other integrity variables to provide more efficient data delivery. The deduplicating algorithm focuses on a combination of four important attributes: Device ID, Latitude, Longitude, and Timestamp. This algorithm scours our data and identifies rows that contain the same combination of these four attributes. Post-identification, it retains a single copy and eliminates duplicate values to ensure our customers only receive complete and unique datasets.

We actively identify overlapping values at the provider level to determine the value each offers. Our data science team has developed a sophisticated overlap analysis model that helps us maintain a high-quality data feed by qualifying providers based on unique data values rather than volumes alone – measures that provide significant benefit to our end-use partners.

Quadrant mobility data contains all standard attributes such as Device ID, Latitude, Longitude, Timestamp, Horizontal Accuracy, and IP Address, and non-standard attributes such as Geohash and H3. In addition, we have historical data available back through 2022.

Through our in-house data science team, we offer sophisticated technical documentation, location data algorithms, and queries that help data buyers get a head start on their analyses. Our goal is to provide you with data that is “fit for purpose”.

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...

Browse LSEG's I/B/E/S Estimates, discover our range of data, indices & benchmarks. Our Data Catalogue offers unrivalled data and delivery mechanisms.

Unlock the Power of Behavioural Data with GDPR-Compliant Clickstream Insights.

Swash clickstream data offers a comprehensive and GDPR-compliant dataset sourced from users worldwide, encompassing both desktop and mobile browsing behaviour. Here's an in-depth look at what sets us apart and how our data can benefit your organisation.

User-Centric Approach: Unlike traditional data collection methods, we take a user-centric approach by rewarding users for the data they willingly provide. This unique methodology ensures transparent data collection practices, encourages user participation, and establishes trust between data providers and consumers.

Wide Coverage and Varied Categories: Our clickstream data covers diverse categories, including search, shopping, and URL visits. Whether you are interested in understanding user preferences in e-commerce, analysing search behaviour across different industries, or tracking website visits, our data provides a rich and multi-dimensional view of user activities.

GDPR Compliance and Privacy: We prioritise data privacy and strictly adhere to GDPR guidelines. Our data collection methods are fully compliant, ensuring the protection of user identities and personal information. You can confidently leverage our clickstream data without compromising privacy or facing regulatory challenges.

Market Intelligence and Consumer Behaviour: Gain deep insights into market intelligence and consumer behaviour using our clickstream data. Understand trends, preferences, and user behaviour patterns by analysing the comprehensive user-level, time-stamped raw or processed data feed. Uncover valuable information about user journeys, search funnels, and paths to purchase to enhance your marketing strategies and drive business growth.

High-Frequency Updates and Consistency: We provide high-frequency updates and consistent user participation, offering both historical data and ongoing daily delivery. This ensures you have access to up-to-date insights and a continuous data feed for comprehensive analysis. Our reliable and consistent data empowers you to make accurate and timely decisions.

Custom Reporting and Analysis: We understand that every organisation has unique requirements. That's why we offer customisable reporting options, allowing you to tailor the analysis and reporting of clickstream data to your specific needs. Whether you need detailed metrics, visualisations, or in-depth analytics, we provide the flexibility to meet your reporting requirements.

Data Quality and Credibility: We take data quality seriously. Our data sourcing practices are designed to ensure responsible and reliable data collection. We implement rigorous data cleaning, validation, and verification processes, guaranteeing the accuracy and reliability of our clickstream data. You can confidently rely on our data to drive your decision-making processes.

Comprehensive dataset containing 55 verified Feed manufacturer businesses in Wisconsin, United States with complete contact information, ratings, reviews, and location data.

Browse LSEG's Events , discover our range of data, indices & benchmarks. Our Data Catalogue offers unrivalled data and delivery mechanisms.

Comprehensive dataset containing 149 verified Animal feed store businesses in Illinois, United States with complete contact information, ratings, reviews, and location data.

In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.

This data providers package provides the data collection configuration and supporting materials for reporting Chemical Contaminants in SSD1. These are to be used for the official data reporting phase.

The package includes:

The Standard Sample Description Version 2 XSD schema definition for CONTAMINANTS reporting.

The general and CONTAMINANTS SSD1 specific business rules applied for the automatic validation of the submitted datasets.

Excel Mapping tool to convert excel files after mapping into XML document.

Please follow the instructions below for the correct use of the mapping tool to avoid compromising its functionalities:

Download and save the MS Excel® Standard Sample Description file to your computer (do not open the file before saving and do not change the file name)

Download and save the file MS Excel® Simplified Reporting Format (do not open the file before saving)

Keep both Excel files in the same folder

Open both Excel files and enable the macros

Keep both files open in the same Excel instance when filling in the data

Guidance on how to run the validation report after submitting data to the DCF.

Access our data for free: https://matrix.blocksize.capital/auth/open/sign-up

Blocksize’s Real-Time Bid/Ask Feed provides an accurate and continuously updated view of market liquidity, aggregating the best bid and ask prices across a broad selection of centralized and decentralized exchanges as well as producing the mid price. Designed for trading platforms, institutional desks, data vendors, and DeFi applications, this feed offers critical insight into price discovery, market depth, and spread dynamics with sub-second latency — all through unlimited WebSocket access.

Each data point is calculated by collecting order book updates across multiple exchanges and applying a volume-weighted averaging algorithm for both bid and ask sides. This ensures the most liquid venues exert greater influence on the final price, providing a more reliable indication of market value than single-source quotes. The resulting feed not only shows top-of-book prices but also reflects the effective trading cost (via spread width) and execution quality available across markets.

To guarantee data quality, Blocksize applies a statistical anomaly filter that dynamically adapts to trading activity. Using a liquidity-adjusted window, the system filters out sudden outliers that could otherwise distort bid or ask prices. In addition, if a significant price jump is detected, a built-in correction mechanism recalibrates the data window to ensure the feed remains responsive without misclassifying valid moves as anomalies.

This product is particularly valuable in low-liquidity markets where last-traded prices may not represent current market value. Traders can use the feed to price assets, optimize order routing, and assess volatility. Meanwhile, oracles, analytics platforms, and institutional clients benefit from clean, real-time insights into the most executable price levels in the market — with guaranteed uptime and consistent update frequency.

Our Customers:

• Oracles & DeFi Protocols and Applications
• Asset & Fund Managers investing in digital assets
• Asset Custodians storing digital assets
• Banks, Brokers with crypto offering
• Traditional Data Providers planning to extend their offering to digital assets
• Information Provider platforms

Questions? Reach out to our qualified data team.

PII Statement: Our datasets does not include personal, pseudonymized, or sensitive user data

In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.

This data providers package provides the data collection configuration and supporting materials for reporting Chemical Contaminants in SSD2. These are to be used for the official data reporting phase.

The package includes:

CHECK advice on the values to be reported for the mandatory fields specified for this data collection.

The Standard Sample Description Version 2 XSD schema definition for CONTAMINANTS reporting.

The STX transformation file which automatically assigns sampEventId and sampAnId when this information is not provided.

The general and CONTAMINANTS SSD2 specific business rules applied for the automatic validation of the submitted datasets.

Excel Mapping tool to convert excel files after mapping into XML document.

Guidance on how to use the Excel Mapping tool.

Guidance on how to run the validation report after submitting data to the DCF.

Quadrant provides Insightful, accurate, and reliable mobile location data.

Our privacy-first mobile location data unveils hidden patterns and opportunities, provides actionable insights, and fuels data-driven decision-making at the world's biggest companies.

These companies rely on our privacy-first Mobile Location and Points-of-Interest Data to unveil hidden patterns and opportunities, provide actionable insights, and fuel data-driven decision-making. They build better AI models, uncover business insights, and enable location-based services using our robust and reliable real-world data.

We conduct stringent evaluations on data providers to ensure authenticity and quality. Our proprietary algorithms detect, and cleanse corrupted and duplicated data points – allowing you to leverage our datasets rapidly with minimal processing or cleaning. During the ingestion process, our proprietary Data Filtering Algorithms remove events based on a number of both qualitative factors, as well as latency and other integrity variables to provide more efficient data delivery. The deduplicating algorithm focuses on a combination of four important attributes: Device ID, Latitude, Longitude, and Timestamp. This algorithm scours our data and identifies rows that contain the same combination of these four attributes. Post-identification, it retains a single copy and eliminates duplicate values to ensure our customers only receive complete and unique datasets.

We actively identify overlapping values at the provider level to determine the value each offers. Our data science team has developed a sophisticated overlap analysis model that helps us maintain a high-quality data feed by qualifying providers based on unique data values rather than volumes alone – measures that provide significant benefit to our end-use partners.

Quadrant mobility data contains all standard attributes such as Device ID, Latitude, Longitude, Timestamp, Horizontal Accuracy, and IP Address, and non-standard attributes such as Geohash and H3. In addition, we have historical data available back through 2022.

Through our in-house data science team, we offer sophisticated technical documentation, location data algorithms, and queries that help data buyers get a head start on their analyses. Our goal is to provide you with data that is “fit for purpose”.

Quadrant provides Insightful, accurate, and reliable mobile location data.

Our privacy-first mobile location data unveils hidden patterns and opportunities, provides actionable insights, and fuels data-driven decision-making at the world's biggest companies.

These companies rely on our privacy-first Mobile Location and Points-of-Interest Data to unveil hidden patterns and opportunities, provide actionable insights, and fuel data-driven decision-making. They build better AI models, uncover business insights, and enable location-based services using our robust and reliable real-world data.

We conduct stringent evaluations on data providers to ensure authenticity and quality. Our proprietary algorithms detect, and cleanse corrupted and duplicated data points – allowing you to leverage our datasets rapidly with minimal processing or cleaning. During the ingestion process, our proprietary Data Filtering Algorithms remove events based on a number of both qualitative factors, as well as latency and other integrity variables to provide more efficient data delivery. The deduplicating algorithm focuses on a combination of four important attributes: Device ID, Latitude, Longitude, and Timestamp. This algorithm scours our data and identifies rows that contain the same combination of these four attributes. Post-identification, it retains a single copy and eliminates duplicate values to ensure our customers only receive complete and unique datasets.

We actively identify overlapping values at the provider level to determine the value each offers. Our data science team has developed a sophisticated overlap analysis model that helps us maintain a high-quality data feed by qualifying providers based on unique data values rather than volumes alone – measures that provide significant benefit to our end-use partners.

Quadrant mobility data contains all standard attributes such as Device ID, Latitude, Longitude, Timestamp, Horizontal Accuracy, and IP Address, and non-standard attributes such as Geohash and H3. In addition, we have historical data available back through 2022.

Through our in-house data science team, we offer sophisticated technical documentation, location data algorithms, and queries that help data buyers get a head start on their analyses. Our goal is to provide you with data that is “fit for purpose”.

Feed Software Market Outlook

The global feed software market size was valued at USD 1.3 billion in 2023 and is projected to reach USD 2.8 billion by 2032, growing at a CAGR of 8.7% during the forecast period. The primary growth factor for this market is the increasing demand for efficient and sustainable feed management solutions across various sectors such as agriculture, livestock management, aquaculture, and pet food manufacturing.

One of the major growth drivers for the feed software market is the rising awareness of the importance of nutrition management in enhancing animal productivity and health. As the global demand for high-quality animal-derived food products continues to rise, farmers and feed manufacturers are increasingly turning to advanced software solutions to streamline their operations, optimize feed formulations, and reduce waste. This trend is particularly notable in developing regions where industrial farming practices are gaining traction.

Moreover, technological advancements and the integration of IoT and AI in feed software solutions are propelling market growth. Modern feed software systems offer data analytics, real-time monitoring, and predictive tools that enable users to make informed decisions and improve operational efficiency. The adoption of such cutting-edge technologies is expected to drive the market further as stakeholders recognize the benefits of improved feed efficiency and cost savings.

The growing trend towards sustainability and environmental conservation is also fueling the demand for feed software. Governments and regulatory bodies worldwide are implementing stringent regulations to minimize the environmental impact of livestock farming, thereby encouraging the adoption of software that can aid in resource optimization and reducing greenhouse gas emissions. This regulatory push, coupled with increasing consumer preference for sustainably produced food products, is anticipated to boost the market during the forecast period.

From a regional perspective, North America and Europe currently dominate the feed software market, attributed to the well-established livestock and agriculture sectors in these regions. However, significant growth is also expected in the Asia Pacific region due to rapid industrialization, increasing population, and rising disposable incomes, which are driving the demand for efficient animal feed solutions. Latin America and the Middle East & Africa are emerging markets with considerable growth potential, supported by government initiatives and investments in the agricultural sector.

Deployment Type Analysis

The feed software market can be segmented by deployment type into on-premises and cloud-based solutions. On-premises deployment involves installing software locally on a company's own servers and computers. This approach provides greater control over data and system security but requires significant upfront investment in hardware and IT infrastructure. Despite these challenges, on-premises solutions remain popular among large enterprises with the necessary resources and a preference for internally managed systems.

Conversely, cloud-based deployment has gained considerable traction in recent years due to its flexibility, scalability, and cost-effectiveness. Cloud-based feed software allows users to access systems remotely via the internet, reducing the need for extensive IT infrastructure and maintenance. This deployment type is particularly advantageous for small and medium-sized enterprises (SMEs) that may not have the financial capacity for substantial initial investments. Additionally, cloud solutions often come with regular updates and support from the service provider, ensuring that users always have access to the latest features and security enhancements.

The adoption of cloud-based feed software is further driven by the increasing availability of high-speed internet and advancements in cloud computing technologies. As more businesses recognize the benefits of cloud solutions, such as improved data accessibility, real-time collaboration, and disaster recovery capabilities, the demand for cloud-based feed software is expected to grow significantly during the forecast period. Furthermore, cloud solutions often offer subscription-based pricing models, making them more accessible to a broader range of users.

Another factor contributing to the growth of cloud-based deployment is the rising emphasis on data-driven decision-making in the agriculture and livestock sectors. Cloud-based feed software can seamle

The global bank feed market is experiencing robust growth, driven by the increasing adoption of cloud-based accounting software and the rising demand for automated financial data management solutions across SMEs and large enterprises. The market's expansion is fueled by several key factors: the need for improved financial accuracy and efficiency, enhanced regulatory compliance requirements, and the desire for real-time financial insights. Direct feed solutions, which offer a seamless integration with banking systems, are witnessing higher adoption rates compared to indirect feeds, reflecting a preference for streamlined and automated processes. Large enterprises, with their complex financial structures, are major contributors to market growth, while the SME segment is also expanding rapidly, fueled by the accessibility and affordability of cloud-based accounting solutions. Geographic variations exist, with North America and Europe currently dominating the market due to higher technological adoption and a well-established fintech ecosystem. However, regions like Asia-Pacific are projected to show significant growth in the coming years driven by increasing digitalization and economic expansion. Competitive pressures are high, with numerous established players and emerging fintech companies vying for market share. The market's future trajectory suggests continued expansion, driven by ongoing technological advancements such as AI-powered data analysis and enhanced security features within bank feed solutions. Despite the promising growth, the market faces certain challenges. Integration complexities with diverse banking systems and data security concerns remain significant hurdles. Furthermore, the reliance on secure APIs and the need for continuous updates to adapt to evolving banking systems and regulations pose ongoing operational challenges for providers. Data privacy regulations like GDPR also influence market dynamics, necessitating robust compliance measures. However, innovative solutions addressing these challenges, coupled with the inherent advantages of automated bank feeds, are expected to mitigate these restraints and sustain market expansion throughout the forecast period. The market's evolution will likely be shaped by partnerships and acquisitions amongst existing players, as well as the entry of new companies with disruptive technologies.

Comprehensive dataset containing 83 verified Animal feed store businesses in Maryland, United States with complete contact information, ratings, reviews, and location data.