Alternative data datasets
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Population and demographic attributes for audience analysis.
A geographic dataset that outlines and labels residential neighborhood boundaries.
Aggregated point-level records combining geographic coordinates with firm details and notable sites.
Aggregated point-level records combining geographic coordinates with firm details and natural or man-made landmarks.
Information on more than 60,000 investment professionals and asset holders worldwide.
Global coverage of over 60,000 fund management firms and investor entities.
Dataset encompassing 60,000-plus investment managers and shareholders across the world.
A large scale collection of structured video annotations covering transcripts, summaries, sentiment, safety signals, and content metadata.
Safety assessment scores for online video content evaluated against eleven distinct risk categories.
Keyword, entity, and IAB category classifications derived from online video content, designed to support contextual ad targeting without relying on cookies.
Analytical outputs capturing sentiment, emotional tone, intensity, and controversial elements found in online video material.
Information sourced from decentralized exchanges, lending platforms, derivatives venues, and broader on-chain blockchain records.
Archive of past performance ratings and related documentation for every skilled nursing facility.
Daily employment trends derived from job listings posted by more than sixty-five thousand companies, sourced via LinkUp.
Organized intelligence drawn from news outlets and social platforms exceeding forty thousand in number, including tone and sentiment analysis.
Clean property boundary lines are offered in both geospatial and spreadsheet-friendly formats.
Consumer-authorized digital behavioral tracking data collected with explicit consent.
Analytical view of staffing patterns and labor movement within individual organizations.
Cleaned and standardized loan-level records from Fannie Mae, Freddie Mac, and Ginnie Mae covering the mortgage-backed securities market.
Cleaned and standardized loan-level records from Fannie Mae, Freddie Mac, and Ginnie Mae covering a 12-month historical window.
Standardized financial statement records aligned with NACE industry classifications, delivered in an analytics-friendly format with rights cleared for machine learning and artificial intelligence development.
Cross-industry financial statement data normalized to NACE codes, pre-processed for analytical use and permitted for training AI and ML models.
Standardized financial statement data aligned with NACE classifications, formatted for analytics and cleared for use in AI and machine learning model development.
NACE-aligned financial reporting records prepared for downstream analytics and authorized for use in artificial intelligence and machine learning model development.
Financial statement information standardized along the NACE taxonomy, packaged for analytical workflows and licensed to support AI and ML training activities.
Industry-coded financial statements harmonized via NACE, supplied in a form ready for analysis and cleared for artificial intelligence and machine learning purposes.
A consolidated set of NACE-mapped financial statements ready for data analysis and permitted to be used in training AI and machine learning models.
NACE-standardized financial statement data, formatted for analytics pipelines and licensed for building AI systems and machine learning algorithms.
Curated financial reporting records classified under NACE, engineered for analytical workloads and licensed for artificial intelligence and machine learning training.
Standardized financial statement data aligned with NACE classifications, formatted for analytics and cleared for use in AI and machine learning model development.
Financial statements aligned to NACE industry categories, structured for analytic consumption and approved for use in AI and ML model training.
NACE-harmonized financial statement datasets delivered in an analytics-ready state with licensing terms covering AI and machine learning model training.
Standardized financial reporting records mapped to NACE industry classifications, prepared for analytics use and cleared for machine learning applications.
Normalized financial indicators for publicly traded companies, reconciled to account for varying reporting standards.
A complete review of carbon capture, utilization, and storage initiatives and the associated supply network.
Cross-country comparison of carbon dioxide emissions from oil and gas fields by nation, operator, and corporate entity.
Market and supply chain information for the geothermal energy sector.
Cross-country, operator, and company-level comparison of CO2 emissions from oil and gas fields worldwide.
Compilation of well and production records featuring the most precise interpreted geological tops and positional information.
Maritime shipment tracking system delivering near real-time cargo data for individual vessels.
S&P Global Energy scenario datasets consolidated for streamlined analytics and faster interpretation.
An LNG Cargo dataset containing core information about worldwide liquefied natural gas shipment movements.
Global freight rate evaluations and marine fuel pricing across multiple commodities.
Information on greenhouse gas emissions originating from upstream operations.
Past and projected weather observations consolidated into a single, regularly refreshed resource.
Generates in-house indicators of credit exposure and trend strength derived from the S&P Global CDS Pricing collection.
Tools for evaluating the credit exposure associated with a counterparty.
An alternative data feed delivering utility as both a sustainability measure and a risk signal for investment professionals.
A structured, multi-level categorization framework distinguishes between ETFs and ETNs through style-based groupings.
An in-depth overview of a firm's employee structure, hiring patterns, and key human-resources indicators.
Independent and open municipal bond price feeds are supplied to assist with transactions, valuation work, and related analysis.
Worldwide supply chain intelligence covering in excess of nine million firms along with more than two billion shipping entries.
Evaluates how individual companies are vulnerable to seven physical hazards linked to climate change.
Applies natural language processing to earnings call transcripts in order to surface KPI-related signals such as risk factors, strategic pivots, and pricing pressures.
Multiple credit risk evaluations are combined into one consolidated score that summarizes an entity's credit standing.
Worldwide estimates derived from modeling, projections, and analytical research efforts.
Company-level environmental, social, and governance ratings, including separate scores for each pillar and the methodology used to derive them.
A broad set of metrics addressing multiple dimensions of supply chain activity.
NLP-derived sentiment ratings and behavioral indicators extracted from corporate transcripts.
Offers full environmental performance records covering more than 16,800 organizations.