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Focused on specific industries like e-commerce and ride-sharing. YipitData Insights offers datasets that are rich in detail and designed for high-frequency trading and institutional investors.
Tools that collect, process, and analyze non-traditional data sources such as satellite imagery, social media sentiment, credit card transactions, and mobile location data to generate investment insights not available from conventional sources.
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Number of Data Sources Total distinct alternative data sources (e.g., satellites, social, POS) the platform integrates. |
No information available | |
Source Diversity Range of data types covered (e.g., geospatial, transactional, web-scraped, sensor data, etc.) |
No information available | |
Data Source Transparency Level of disclosure around data origins and collection methods. |
Company provides detailed documentation and transparency into methodology for each data set (visible on their website). | |
Coverage Geography Geographical breadth of alternative data (e.g., global, regional, local markets). |
No information available | |
Historical Depth Amount of historical data available for backtesting and longitudinal analysis. |
No information available | |
Source Update Frequency How often new data is ingested from sources. |
No information available | |
Exclusive or Unique Sources Whether the platform provides access to otherwise unavailable/uncommon datasets. |
No information available | |
Source Verification Processes in place to verify data authenticity and quality. |
YipitData has established processes for data verification evidenced by their methodology documentation for institutional investors. | |
Consent & Compliance Ensures data sources are ethically and legally obtained with proper user consent. |
Obtains data only from legal, privacy-compliant sources; statement of compliance and consent practices available on site. | |
Real-Time Data Availability Whether some or all data sources provide real-time or near-real-time feeds. |
Offers near-real-time or daily updates for certain datasets as shown in product documentation. | |
Unstructured Data Handling Ability to process and integrate unstructured data such as images or text. |
Extracts and analyzes unstructured web data (e.g., receipts, reviews, product pages). | |
Data Licensing Terms Clarity Transparency and clarity of the licensing rights and restrictions regarding data use. |
Data use is governed by clear contractual terms; references to licensing terms for enterprise clients. |
Error Rate Frequency of data processing or reporting errors. |
No information available | |
Missing Data Handling Systematic mitigation of gaps or missing values in data streams. |
Handles data inconsistencies; imputation, gap filling, and QA described in documentation. | |
Data Normalization Standardization of datasets for ease of analysis. |
Standardizes data fields for easier institutional analysis. Each dataset description notes normalization. | |
Data Granularity Level of detail available (e.g., hourly, daily, per store, per SKU). |
No information available | |
Quality Assurance Processes Robustness of quality control and regular audits. |
YipitData states ongoing QA and auditing in support materials. | |
Latency Time delay between data creation and its availability on the platform. |
No information available | |
Deduplication Automated detection and removal of duplicate entries. |
Describes de-duplication and anomaly filtering as part of data pipeline, referenced in methodology documentation. | |
Anomaly Detection System flags and explains outliers or errors in incoming data. |
Uses statistical models to highlight outliers and data issues for analysts. | |
Imputation Techniques Advanced strategies for predicting and filling missing data. |
Employs imputation when needed, as discussed in technical whitepapers. | |
Version Control Ability to track changes and updates to datasets for auditability. |
Tracks dataset versions and methodology changes for auditable client use. |
Prebuilt Analytics Number of out-of-the-box analytical models or dashboards for typical investment use cases. |
No information available | |
Custom Analysis Capability Ability to build custom models or queries on platform data. |
Enables clients to build their own models and queries using granular data provided. | |
Correlation Analysis Supports finding relationships between alternative data and traditional financial metrics. |
Enables linking alternative data to traditional KPIs through analytic tools. | |
Backtesting Tools Built-in functionality for testing investment hypotheses using historical data. |
Backtesting is a key reported use case for institutional clients—supported in dataset access. | |
Predictive Modeling Availability of machine learning or AI-driven forecasting modules. |
Proprietary forecasting and ML models advertised for institutional investors. | |
Sentiment Analysis Detects and quantifies market sentiment from textual or social media data. |
Provides sentiment indicators (e.g., review-based sentiment) for certain tracked companies. | |
Geospatial Analytics Ability to map and analyze spatial data (e.g., satellite imagery). |
Some products integrate geospatial analytics (such as location-based use in mobility platforms). | |
Real-Time Alerting Automatic notification of significant changes or anomalies relevant to portfolio holdings. |
No information available | |
Enrichment with Traditional Data Integrated blending of alternative and conventional financial data sets. |
Blends alternative data with public/financial data for richer insight. | |
Explainability of Models Features supporting interpretability of predictive signals and models. |
Provides guidance on model explainability and shares methodology and interpretability details. | |
Scalability of Analytics Ability for analytic tools to function with large and growing data sets. |
Designed for scalability for institutional clients; high-volume data processing and analytics described in technical materials. |
API Availability Provision of programmatic data and analytics access via APIs. |
API/data access widely advertised for integration with downstream client systems. | |
Standard Data Connectors Prebuilt connectors to common analytics, BI, or portfolio management tools. |
Has connectors to major platforms and portfolio management solutions (per sales materials). | |
Bulk Data Export Support for exporting large batches of raw or processed data. |
Data can be exported in bulk for client use cases, according to product docs. | |
Real-time Streaming Integration Ability for real-time data feeds to integrate into live workflows. |
No information available | |
Cloud Storage Integration Compatibility with popular cloud storage solutions (AWS, Azure, GCP, etc.). |
Supports S3, Azure, and other cloud storage integration for enterprise deliveries. | |
Role-Based Access Control Enables fine-grained access management for different organizational users. |
Large enterprise clients can set role-based permissions for access to datasets. | |
User Interface Usability Intuitive and efficient user interface for analysts and developers. |
Web interface and API are highly regarded for ease of use in analyst reviews. | |
Mobile Access Functional accessibility from mobile devices (native apps or web). |
No information available | |
White-Labeling Possibility to customize the platform to align visually and functionally with client brand. |
No information available | |
SDK Availability Provision of software development kits for easier custom integration. |
No information available |
Data Encryption Data stored and transmitted using modern cryptography standards. |
Data is encrypted in transit and at rest as per compliance documents. | |
Audit Logging Maintains a complete log of access and actions for compliance. |
Provides detailed logging and audit trails for enterprise clients. | |
Regulatory Certifications Possession of certifications such as GDPR, CCPA, SOC2 relevant to data compliance. |
Compliant with GDPR, CCPA, SOC2; certifications listed. | |
User Access Controls Granular user and group-based permissioning on data and analytics. |
Admin features support granular access setups for datasets and analytic functions. | |
Penetration Testing Regular vulnerability/pentesting assessments are performed. |
No information available | |
Privacy Protection Guarantees regarding data subject anonymity and privacy protection. |
Specifically calls out privacy protection and anonymization for all individuals in data sets. | |
Data Residency Options Ability to specify jurisdictions where data is stored or processed. |
No information available | |
Third-party Data Sharing Controls Restrictions/controls over redistribution of consumed data. |
Restricts redistribution of data by clients per license agreements. | |
Security Incident Notification Automated alerting regarding breaches or suspicious activity. |
No information available | |
Vendor Diligence Support Facilitates client due diligence workflows (DDQ, supporting docs, etc). |
Supports client due diligence; makes available technical supporting documentation and DDQ responses. |
Concurrent User Capacity Maximum number of active users supported simultaneously. |
No information available | |
Query Response Time Median time taken to return analytics or data queries. |
No information available | |
Data Ingestion Rate Volume of new data processed per unit of time. |
No information available | |
Uptime SLA Service Level Agreement (SLA) on platform operational uptime. |
No information available | |
Peak Data Storage Capacity Maximum volume of data the platform can host. |
No information available | |
Elastic Compute Scaling Automatic scaling of compute resources to match workload. |
Back end scales to client demand; elastic compute for institutional data processing. | |
Parallel Processing Support Ability to process multiple data streams or queries concurrently. |
Processes multiple concurrent requests for large client organizations. | |
Data Retention Policy Flexibility Configurable data storage retention periods. |
Enables clients to configure their own retention periods for extracted datasets. | |
Performance Monitoring Tools Built-in dashboards or reporting for platform health and performance. |
Platform provides dashboards and detailed reporting on platform health, available to enterprise users. | |
Batch Processing Support Efficient support for large batch data operations. |
Provides batch data export/processing for historical and backtesting use cases. |
Onboarding Support Personalized setup, initial training, and account configuration help. |
Offers onboarding support and onboarding sessions for institutional clients. | |
Knowledge Base Extensive searchable documentation and tutorials. |
Comprehensive search and tutorials available for users (see support center and product guides). | |
Data Dictionary Comprehensive descriptions of each data field and its origin. |
Supplies detailed data dictionaries for each dataset. | |
API Documentation Completeness Detail and clarity of technical integration guidelines. |
API documentation is detailed and accessible for all subscribers. | |
Dedicated Account Management Assigned customer success managers for enterprise users. |
Enterprise clients receive dedicated account management. | |
Live Chat Support Immediate support via chat with platform staff. |
No information available | |
User Training Workshops Regularly scheduled or on-demand platform training. |
Delivers regular and on-demand user training for clients, as described in support materials. | |
Community Forum User-to-user interaction and support hub. |
No information available | |
Localization Support Availability in multiple languages and time zones. |
No information available | |
Feedback Mechanism Ability for users to suggest features or report issues and track resolution. |
No information available |
Usage-Based Pricing Option for pricing tied to volume or levels of consumption. |
No information available | |
Tiered Subscription Models Multiple service tiers for diverse needs and budgets. |
Multiple subscription levels for enterprise and other clients advertised on site. | |
Custom Enterprise Agreements Ability to negotiate bespoke terms for large clients. |
Custom terms and enterprise contracts available, based on product description. | |
Transparent Fee Structures Upfront and clear disclosure of fees across all services. |
Fee model is transparent, with no hidden charges per product documentation. | |
Free Trial Availability Short-term trial or demo use before commitment. |
No information available | |
Minimum Contract Term Shortest term for standard agreements. |
No information available | |
Add-On Modules Pricing Clarity and flexibility of pricing for optional advanced modules. |
No information available | |
Early Termination Options Availability of low-penalty or pro-rata contract cancellation. |
No information available | |
Unlimited User Pricing Flat-rate pricing not tied to user count. |
No information available | |
Nonprofit/Educational Discounts Special pricing for academic or nonprofit organizations. |
No information available |
Custom Dashboard Building Ability to design and save custom dashboards for specific analyses. |
Provides custom dashboards tailored to institutional client needs. | |
Workflow Automation Integration with tools for process automation (e.g., alerts, trade signals). |
Can trigger automated analyses and custom alerts based on data events. | |
Custom Data Ingestion Upload and merge a client’s own alternative or proprietary data. |
Clients can upload and integrate own datasets via platform. | |
Plugin/Extension Framework Ability to add modules/extensions for new functionalities. |
No information available | |
Scripting/Programming Interface Support for custom script development (e.g., Python, R APIs). |
APIs and scripting interfaces (e.g., Python) supported for model development. | |
Theming/Branding Customization Visual customization for brand consistency. |
Supports visual theming for client organizations. | |
Custom Reporting Design and automate custom report formats. |
Automated and custom report formats available. | |
Alert Customization User-defined conditions and triggers for event-driven alerts. |
Clients can define custom analytic and alerting triggers. | |
Integration with In-House Tools Ability for organization-specific connectors/modules. |
Supports integration with select clients' in-house tools via API and standard connectors. | |
Deploy in Private Cloud Support for on-premises or VPC deployment for sensitive clients. |
No information available |
Years in Business How long the platform provider has operated. |
No information available | |
Referenceable Clients Number of notable clients willing to provide references. |
No information available | |
Third-Party Reviews Number and quality of external analyst or customer reviews. |
No information available | |
Legal Disputes Disclosed History of significant legal action or unresolved disputes. |
No major legal disputes disclosed; no controversies found in legal news or press. | |
Financial Transparency Annual financial reporting or third-party audits available. |
Company provides transparency on funding, as well as some annual reporting; third-party audits referenced. | |
Industry Partnerships Participation in alliances or consortia that enhance credibility. |
Partners with other data and analytics providers in the financial sector. | |
Churn Rate Percentage of clients discontinuing service per year. |
No information available | |
Client Growth Rate Annual increase in platform users or logos. |
No information available | |
Awards/Industry Recognition Recognition by reputable industry organizations. |
Has received multiple Capital Markets awards and fintech recognitions. | |
Business Continuity Plan Documented and tested plans for disaster recovery and service resilience. |
Maintains a business continuity/disaster recovery plan for institutional clients. |
AI/ML Model Upgrades Frequency of innovation or upgrades in analytic and predictive engines. |
No information available | |
New Data Source Integration Rate How quickly new alternative data sources are made available to users. |
No information available | |
Participates in Data Consortiums Active member of data-sharing or standards organizations. |
Participates in industry groups for standardizing alt data practices. | |
Visualization Innovation Frequency of new or advanced visualization techniques introduced. |
No information available | |
Beta Testing/Client Feature Input Mechanisms for early adopter programs or client-driven roadmap. |
No information available | |
Academic Collaborations Partnerships with universities for applied research. |
No information available | |
Open Data Initiatives Support or contribution to open alternative data/tech communities. |
No information available | |
Data Science Sandbox Environment for clients to experiment with new data and analytics. |
No information available | |
API Versioning and Roadmap Disclosure Transparent release plans and versioning for APIs and tech. |
API versioning managed and future roadmap sometimes disclosed to select clients. | |
Cross-Asset Data Opportunities Support for new data categories relevant across markets (e.g., ESG, crypto). |
Supports ESG factors, crypto tracking, and cross-sector analysis. |
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