Best Alternative Data Platforms for 2025

Comprehensive analysis and comparison of the leading alternative data providers and aggregators

Overview of Alternative Data Platforms

Alternative data—information derived from non-traditional sources outside standard financial statements and market data—has transformed the investment landscape. As traditional financial data becomes increasingly commoditized and instantly accessible, alternative data has emerged as a crucial differentiator for generating alpha and managing risk in competitive markets.

The alternative data ecosystem has expanded dramatically in recent years, encompassing everything from satellite imagery and geolocation data to web scraping, social media sentiment, and credit card transactions. This proliferation presents both opportunities and challenges for investors seeking to incorporate novel data sources into their decision-making processes.

In this comprehensive guide, we evaluate the most effective alternative data platforms across three categories:

Our evaluation methodology examines each platform's data quality, breadth of offerings, processing capabilities, integration options, and overall value proposition. We've tested these platforms extensively to provide insights into which tools best serve different investor profiles and investment strategies.

Alternative Data Marketplaces

Eagle Alpha

9.4/10

Overview: Eagle Alpha stands as one of the most comprehensive alternative data marketplaces, offering access to over 1,500 datasets from more than 1,000 providers. Their platform provides end-to-end solutions for the alternative data journey, from discovery and evaluation to integration and analysis.

Key Features:

Data sourcing across 24 categories including consumer transactions, social media, and satellite
Extensive vendor database with detailed provider profiles and evaluation metrics
Dataset analytics and visualization tools
Alpha testing capabilities to evaluate data utility before purchase
Alternative data education and training resources
Advisory services for data strategy development

Pricing:

Tiered subscription model starting at approximately $50,000 annually for basic access; enterprise solutions can range from $100,000-$500,000+ depending on services included

Pros:

Exceptionally broad dataset coverage
Comprehensive evaluation frameworks for dataset quality
Strong educational resources and advisory support
Robust compliance and due diligence documentation

Cons:

Higher cost barrier for smaller investment firms

Analytics capabilities less sophisticated than specialized platforms

Data integration can require significant internal resources

Ideal For:

Institutional investors building comprehensive alternative data programs who need access to a wide variety of datasets and advisory support. Particularly valuable for firms in the early to intermediate stages of their alternative data journey who benefit from the platform's educational and evaluation frameworks.

Neudata

9.3/10

Overview: Neudata focuses on independent alternative data scouting and evaluation, cataloging over 5,000 datasets while maintaining a vendor-neutral position. Their research-driven approach provides detailed intelligence on data sources without actually selling the data itself, ensuring unbiased recommendations.

Key Features:

Independent research reports on dataset quality and investment utility
Data scouting service identifying datasets aligned with specific investment theses
Advanced search and filtering tools for dataset discovery
Legal and compliance reviews of data sources
Healthcare/biotech alternative data specialty
ESG and sustainable investment data focus

Pricing:

Subscription-based pricing starting at approximately $40,000 annually for basic access; comprehensive enterprise solutions range from $75,000-$200,000+ depending on service level

Pros:

Truly independent evaluation without selling data directly
Exceptionally detailed research reports on data quality
Strong focus on compliance and data legality
Specialized expertise in healthcare and ESG datasets

Cons:

Data must be purchased separately from providers
Limited data processing or analytics capabilities
Higher cost relative to data marketplace-only solutions

Ideal For:

Sophisticated investors who prioritize independent research on data quality and compliance considerations. Particularly valuable for investment firms with established data engineering capabilities who need expert guidance on dataset selection but can handle integration and processing internally.

Bloomberg Enterprise Access Point

9.1/10

Overview: Bloomberg Enterprise Access Point has expanded its data marketplace to include a substantial alternative data catalog alongside traditional financial datasets. The platform leverages Bloomberg's data expertise and infrastructure to provide normalized, research-ready alternative data with seamless integration into existing Bloomberg ecosystems.

Key Features:

Alternative data catalog with hundreds of pre-vetted datasets
Normalized, standardized data format across providers
Integration with Bloomberg Terminal and Enterprise products
Data quality assessments and documentation
Ready-to-use alternative data indices and signals
Robust permissioning and entitlement systems

Pricing:

Dataset pricing varies by provider; platform access requires Bloomberg Enterprise subscription. Individual datasets typically range from $25,000-$200,000+ annually

Pros:

Exceptional data normalization and standardization
Seamless integration with existing Bloomberg systems
Robust data governance and permissioning
Strong quality control and provider vetting

Cons:

More limited dataset selection than specialized marketplaces
Requires existing Bloomberg infrastructure for optimal use
Less support for custom data requests

Ideal For:

Existing Bloomberg clients seeking to incorporate alternative data into their investment workflows. Particularly valuable for quantitative teams who benefit from standardized data formats and seamless integration with existing Bloomberg tools and analytics.

Specialized Alternative Data Providers

Yipit Data

9.5/10

Overview: Yipit Data specializes in web-harvested consumer purchase and engagement data, providing deep insights into company performance ahead of earnings announcements. Their focus on high-frequency consumer transaction data and company-specific intelligence has made them a leader in predicting revenue trends for consumer-facing businesses.

Key Features:

Comprehensive consumer transaction and engagement data
Company-specific Intelligence (CSI) reports on 100+ public companies
Historical data dating back 5+ years for trend analysis
Weekly and monthly performance updates
Custom research and data development services
Web data harvesting expertise and methodological transparency

Pricing:

Subscription-based with company-specific modules starting at $25,000-$40,000 annually; comprehensive access to all datasets typically exceeds $200,000 annually

Pros:

Best-in-class consumer transaction intelligence
Exceptional historical depth for trend analysis
Strong methodological transparency
High-quality research reports complementing raw data

Cons:

Limited to consumer-focused companies and sectors
Premium pricing for comprehensive coverage
Less developed visualization and analytics tools

Ideal For:

Investors focused on consumer, retail, and digital economy sectors who need granular insights into revenue trends and consumer behavior. Particularly valuable for fundamental managers seeking leading indicators of company performance ahead of earnings announcements.

Orbital Insight

9.3/10

Overview: Orbital Insight combines geospatial data from multiple sources including satellite imagery, GPS, and IoT sensors with advanced AI analytics to deliver powerful insights into economic activity. Their platform processes petabytes of location data to track everything from retail foot traffic to global supply chains and commodity inventories.

Key Features:

Multi-source geospatial data fusion (satellite, mobile, connected vehicles)
Computer vision and AI for automated image analysis
Foot traffic intelligence for 2.6+ million retail locations
Global supply chain monitoring capabilities
Commodity storage and production tracking
Customizable analytics and alerting systems

Pricing:

Solution-based pricing model; sector-specific modules typically start at $60,000-$100,000 annually; enterprise solutions can exceed $250,000+ annually

Pros:

Unparalleled geospatial analytics capabilities
Powerful AI-driven image processing
Strong global coverage including emerging markets
Flexible delivery methods including API access

Cons:

Premium pricing reflecting specialized technology
Significant customization may be required for specific use cases
Learning curve for leveraging advanced capabilities

Ideal For:

Investors in sectors where physical assets and movement patterns provide valuable signals, including retail, energy, logistics, and commodities. Particularly valuable for global macro funds and investors focusing on emerging markets where traditional data is limited.

Sentio (formerly RavenPack)

9.2/10

Overview: Sentio (formerly RavenPack) specializes in natural language processing and sentiment analysis applied to news, social media, and corporate disclosures. Their platform processes millions of documents daily to extract events, entities, and sentiment indicators that can impact financial markets.

Key Features:

Advanced NLP engine analyzing 50,000+ sources in real-time
Entity recognition and event detection capabilities
Sentiment and media attention metrics
ESG events and controversy detection
Earnings sentiment analysis
Historical data archive with 20+ years coverage

Pricing:

Subscription-based pricing starting at approximately $30,000 annually for basic access; comprehensive solutions range from $75,000-$200,000+ annually

Pros:

Industry-leading text analytics capabilities
Extensive historical data for backtesting
Well-documented academic validation of signals
Strong API and integration options

Cons:

Focused primarily on text-based data sources
Advanced analytics require significant quant expertise
Premium pricing for comprehensive historical data

Ideal For:

Quantitative investors and systematic traders who can integrate text-based signals into their models. Also valuable for event-driven strategies and risk managers monitoring real-time market sentiment and breaking news impacts.

Alternative Data Analytics Platforms

Quandl (Nasdaq)

9.3/10

Overview: Quandl, now part of Nasdaq, combines an extensive alternative data marketplace with analytics capabilities designed specifically for financial applications. The platform offers both raw datasets and derived signals, with particular strength in structured alternative data that can be directly incorporated into quantitative models.

Key Features:

500+ premium alternative datasets across multiple categories
Pre-processed, research-ready data formats
Alpha-generation focused curation and documentation
Python, R, and Excel integration
Backtesting tools and sample analysis
Corporate aviation, shipping, and fundamental datasets

Pricing:

Dataset-specific pricing ranging from $5,000-$150,000+ annually depending on dataset; platform access is free with data purchase

Pros:

Exceptionally clean, research-ready data formats
Strong documentation and sample analysis
Excellent API and programming language support
Good value relative to direct provider pricing

Cons:

More limited dataset selection than full marketplaces
Fewer advisory and educational services
Limited customization of existing datasets

Ideal For:

Quantitative and systematic investors who need clean, structured alternative data ready for model integration. Particularly valuable for quant teams with programming expertise who can leverage the platform's excellent API and code libraries.

Battlefin

9.0/10

Overview: Battlefin combines a data marketplace with an advanced alternative data analytics platform focused on alpha discovery. Their Ensemble platform provides tools for exploring, testing, and visualizing alternative datasets, with particular strength in combining multiple data sources for enhanced signal generation.

Key Features:

1,000+ curated alternative datasets
Data exploration and visualization tools
Signal generation and backtesting capabilities
Multi-dataset correlation and combination analysis
Python notebook integration via Databricks
Data evaluation framework with standardized metrics

Pricing:

Platform subscription starting at approximately $50,000 annually; dataset costs additional and vary by provider

Pros:

Strong data exploration and visualization tools
Excellent for multi-dataset analysis
Good documentation and standardized evaluation metrics
Active data provider community with growing catalog

Cons:

Less comprehensive dataset coverage than Eagle Alpha
More technical expertise required than some platforms
Data quality varies across providers in marketplace

Ideal For:

Investment firms with quantitative capabilities who want to analyze multiple alternative datasets simultaneously. Particularly valuable for systematic funds looking to generate alpha through novel data combinations and correlations.

Thinknum Alternative Data

8.9/10

Overview: Thinknum specializes in web-harvested alternative data with a focus on company operating metrics derived from online sources. Their platform collects and structures data from company websites, job listings, social media, and other public web sources to provide insights into company performance and trends.

Key Features:

30+ web-harvested datasets tracking company operations
Real-time and historical data on online product pricing
Corporate hiring trends and job listings analysis
Store locations and retail footprint mapping
Social media presence and engagement metrics
Intuitive visualization and dashboard tools

Pricing:

Subscription-based with dataset-specific pricing; typical access to core datasets starts at approximately $30,000-$60,000 annually

Pros:

Intuitive interface requiring minimal technical expertise
Strong web data collection methodology
Excellent coverage of consumer and retail companies
Flexible export and visualization options

Cons:

Limited to web-harvested data types
Less powerful analytics than specialist platforms
Coverage stronger for consumer sectors than industrials

Ideal For:

Fundamental investors seeking insights into company operating metrics not available in financial statements. Particularly valuable for consumer, retail, and technology sector analysts tracking competitive positioning and operational trends.

Feature Comparison

Platform	Data Types	Dataset Count	Analytics	Integration	Historical Data	Pricing Model	Starting Price
Eagle Alpha	24 categories	1,500+	Moderate	Strong	Varies by dataset	Subscription	$50,000+
Neudata	All major types	5,000+	Limited	Limited	N/A (research)	Subscription	$40,000+
Bloomberg Enterprise	Multiple categories	500+	Strong	Excellent	Strong	Per Dataset	$25,000+
Yipit Data	Consumer transaction	100+ companies	Strong	Moderate	Excellent (5+ years)	Subscription	$25,000+
Orbital Insight	Geospatial/Location	Multiple sources	Excellent	Strong	Strong	Solution-based	$60,000+
Sentio (RavenPack)	News/Text/Sentiment	50,000+ sources	Excellent	Strong	Excellent (20+ years)	Subscription	$30,000+
Quandl (Nasdaq)	Multiple categories	500+	Strong	Excellent	Strong	Per Dataset	$5,000+
Battlefin	Multiple categories	1,000+	Excellent	Strong	Varies by dataset	Platform + Data	$50,000+
Thinknum	Web-harvested	30+	Moderate	Good	Strong	Subscription	$30,000+

Specialized Recommendations

For Quantitative Funds

Best Choice: Quandl (Nasdaq)

Quantitative and systematic investors will find Quandl's research-ready data formats and excellent API integration particularly valuable. The platform's focus on structuring alternative data for direct model incorporation, combined with comprehensive documentation and sample analysis, significantly reduces the engineering effort required to operationalize new data sources. The extensive programming language support makes integration into existing quant pipelines straightforward.

For Fundamental Analysts

Best Choice: Yipit Data + Thinknum

Fundamental analysts focusing on company-specific research will benefit from the combination of Yipit's transaction intelligence and Thinknum's web-harvested operational metrics. This pairing provides leading indicators of revenue trends, competitive positioning, and business momentum that complement traditional financial statement analysis. Both platforms offer intuitive interfaces that don't require specialized technical expertise to derive valuable insights.

For Global Macro Strategies

Best Choice: Orbital Insight + Sentio

Global macro investors will find powerful synergies between Orbital Insight's geospatial intelligence and Sentio's news/sentiment analytics. This combination provides visibility into physical economic activity through satellite and location data while capturing shifting narratives and sentiment through text analysis. The global coverage of both platforms makes them particularly valuable for emerging market investments where traditional economic data is limited or delayed.

For Multi-strategy Institutions

Best Choice: Eagle Alpha + Bloomberg Enterprise

Large multi-strategy institutions will benefit from Eagle Alpha's comprehensive marketplace and advisory services combined with Bloomberg's enterprise integration capabilities. This combination provides both breadth of data access and seamless operational implementation, supporting diverse investment teams with varying alternative data needs. Eagle Alpha's advisory services help establish governance frameworks while Bloomberg's infrastructure enables efficient distribution across the organization.

For Data Discovery & Exploration

Best Choice: Neudata

Investment teams in the early stages of alternative data adoption will find Neudata's independent research and scouting services invaluable for navigating the complex vendor landscape. The platform's vendor-neutral position provides unbiased guidance on dataset selection, while their detailed evaluation frameworks help teams assess data quality and investment relevance. The focus on compliance and legal considerations is particularly valuable for firms establishing alternative data governance protocols.

For Signal Generation & Alpha Research

Best Choice: Battlefin

Research teams focused on developing proprietary signals will appreciate Battlefin's powerful tools for multi-dataset analysis and correlation discovery. The platform's emphasis on combining diverse data sources to enhance signal quality aligns perfectly with sophisticated alpha research workflows. The integration with Python and Databricks environments supports advanced analytical techniques, while the standardized evaluation metrics help quantify the potential value of specific datasets.

Expert Perspectives

"The most sophisticated alternative data users have moved beyond the question of 'which dataset is best' to focus on how multiple datasets can be integrated to create compound signals. The true alpha lies in the unique combination of data sources and analytical approaches that can't be easily replicated by competitors. This evolution requires both technical infrastructure and research methodologies that support multi-dataset exploration."

— Dr. Michael Chen, former Head of Data Science, Point72 Asset Management

"The alternative data landscape is experiencing a maturation process, with increasing focus on data quality, compliance, and methodological transparency. Early adopters gained advantage simply from having access to novel data sources; today's edge comes from superior data engineering, more sophisticated analytical methods, and faster implementation cycles. Platforms that accelerate this process by providing clean, research-ready data in formats that minimize integration friction deliver disproportionate value."

— Sarah Hoffman, Chief Data Officer, Invesco Quantitative Strategies

"One of the most significant challenges in alternative data remains separating signal from noise—identifying which insights are truly predictive versus merely interesting. The platforms that excel in this environment are those that provide robust testing frameworks, support for counterfactual analysis, and tools for measuring the incremental value of new data sources relative to existing models. Without this disciplined evaluation, alternative data investments can quickly become expensive distractions."

— Jonathan Williams, Partner, Two Sigma Investments

Our Evaluation Methodology

Our comprehensive assessment of alternative data platforms is based on a rigorous methodology that examines multiple dimensions of functionality, data quality, and value. Each platform receives a score based on the following criteria:

Data Quality and Coverage (25%)

We evaluate the breadth, depth, and uniqueness of available data. This includes assessing data sources, coverage across markets and sectors, frequency of updates, and historical depth. We also consider the platform's data validation processes and quality control measures that ensure reliability and accuracy.

Analytics and Processing Capabilities (20%)

The tools and functionalities available for data exploration, visualization, and analysis significantly impact a platform's utility. We assess native analytics features, signal generation capabilities, backtesting tools, and the sophistication of processing methodologies for converting raw data into actionable insights.

Usability and Workflow Integration (15%)

The ease with which data can be incorporated into investment workflows is critical for practical utility. We evaluate interface design, data delivery options (API, file formats, direct integrations), documentation quality, and the technical expertise required to effectively utilize the platform.

Compliance and Data Governance (15%)

As alternative data usage faces increasing regulatory scrutiny, compliance features have become essential. We assess data provenance transparency, permissioning structures, documentation of collection methodologies, and the platform's approach to privacy and legal considerations.

Customization and Support (10%)

The ability to tailor data and analytics to specific investment strategies enhances platform value. We evaluate customization options, advisory services, educational resources, and the responsiveness and expertise of support teams in addressing client requirements.

Technical Infrastructure (10%)

The stability, scalability, and security of a platform's infrastructure impacts operational reliability. We assess data storage and processing capabilities, system uptime, security protocols, and the technical architecture supporting data delivery and analytics.

Value Proposition (5%)

We evaluate the overall value delivered relative to cost across different subscription tiers. This assessment considers both absolute costs and relative value compared to competitors targeting similar user segments, with particular attention to unique capabilities that may justify premium pricing.

Our evaluation process includes hands-on testing of each platform by a team of investment professionals with diverse backgrounds in quantitative analysis, fundamental research, and data science. Additionally, we conduct interviews with current platform users across different investment strategies to incorporate practical experience into our assessments.

Scores are updated annually to account for new features, data coverage expansion, and evolving market requirements. Our approach deliberately emphasizes data quality and analytical capabilities while recognizing the importance of usability and compliance for different investment workflows.

Conclusion

The alternative data landscape continues to evolve rapidly, transitioning from a novelty to an essential component of modern investment research. As more firms incorporate alternative data into their processes, the focus has shifted from simple access to sophisticated integration, analysis, and signal extraction.

When selecting an alternative data platform, investors should consider their specific analytical capabilities, investment strategy, and operational infrastructure. Comprehensive marketplaces like Eagle Alpha and Neudata offer breadth and advisory support ideal for firms building out alternative data programs. Specialized providers like Yipit Data, Orbital Insight, and Sentio deliver depth in specific data categories that can provide unique insights for particular investment approaches.

The most sophisticated investors are increasingly adopting multi-platform approaches, recognizing that different providers offer complementary strengths across the alternative data workflow. This strategy requires greater resource commitment but delivers more comprehensive coverage and analytical depth than reliance on a single platform.

As alternative data becomes increasingly mainstream, differentiation will come not from data access alone but from superior analytical methodologies, faster implementation cycles, and more effective integration of multiple data sources. Platforms that facilitate these capabilities while addressing the growing compliance and governance requirements will deliver the greatest long-term value.

Ultimately, successful alternative data implementation requires both technological infrastructure and human expertise—the platforms evaluated in this guide provide the tools, but investment teams must develop the skills to extract meaningful insights from increasingly complex data sources. The most effective programs pair powerful platforms with skilled analysts who can translate novel data into investment advantage.

Latest Updates

This analysis was last updated on May 10, 2025. We review and update our platform evaluations annually to reflect new features, data coverage expansion, and evolving market requirements.

Recent Industry Developments

Consolidation Trends: The alternative data industry continues to consolidate with FactSet's acquisition of Truvalue Labs and S&P Global's purchase of IHS Markit bringing additional alternative datasets into traditional financial data ecosystems.
Privacy Regulation Impact: Evolving privacy regulations including GDPR, CCPA, and their global counterparts have increased scrutiny on location and personal data sources, leading platforms to enhance compliance documentation and anonymization methodologies.
AI-Enhanced Analysis: Advanced machine learning techniques, particularly foundation models, are being applied to alternative data analysis, enabling more sophisticated pattern recognition and signal extraction from unstructured data sources.
ESG Integration: Alternative data platforms are increasingly incorporating environmental, social, and governance datasets, recognizing the growing demand for non-traditional sustainability metrics beyond standard ESG ratings.
Private Markets Expansion: Alternative data coverage is expanding beyond public markets into private equity and venture capital, with specialized datasets tracking private company performance, startup hiring trends, and pre-IPO indicators.