Quality Standards
High-quality data is essential for accurate analysis, informed decision-making, and deriving maximum value. This document describes Twelve Data's data quality standards, explaining our commitment to maintaining high-quality, reliable, and accessible data tailored to users' real-world business needs.
Twelve Data offers comprehensive financial data solutions, including real-time and historical data spanning intervals from 1-minute to 1-month. We provide institutional-grade low latency (170ms) data streaming via WebSocket, ensuring timely and reliable data delivery. Integration is quick and effortless, supported by our API, SDKs, and spreadsheet add-ins, providing unified access to high-precision data across global markets and cryptocurrency exchanges.
API integration is a seamless process, taking just a few minutes with our SDKs and spreadsheet add-ins. Gain access to high-precision data from all cryptocurrency exchanges, conveniently delivered through a single API in a unified format.
Twelve Data adheres to widely accepted data quality dimensions, redefining their fundamental concepts to align with real-world business needs. Each dimension is further broken down into specific elements, each with its own set of quality indicators to ensure precision and reliability.
Data Quality Framework
We adhere to a comprehensive two-layer data quality framework built around five core dimensions:
Dimension | Elements Included |
Availability | Accessibility, Authorisation, Timeliness |
Usability | Definition/Documentation, Metadata, Credibility |
Reliability | Accuracy, Consistency, Completeness, Integrity, Auditability |
Relevance | Fitness |
Presentation Quality | Readability, Structure |
Detailed dimension breakdown
Availability
Ensures data and information are readily accessible and timely.
Accessibility: Data available via JSON/CSV and WebSocket formats, ensuring broad compatibility and seamless access.
Authorisation: Robust API-based data access control.
Timeliness: Data regularly updated; flexible retrieval intervals to meet specific user requirements.
2. Usability
Data must be user-friendly, practical, and clearly documented.
Definition/Documentation: Comprehensive documentation detailing data structure, source, and usage.
Metadata: Clear metadata provided to aid understanding and usability.
Credibility: Data sourced exclusively from reputable, internationally recognized organisations, verified through regular specialist audits.
3. Reliability
Data accuracy, consistency, completeness, and integrity are fundamental.
Accuracy: Continuous specialist checks and automated technical validation.
Consistency: Data values, formats, and definitions remain consistent post-processing; verified through historical reconciliation with third-party sources.
Completeness: Data provided comprehensively, with standardised handling of potential gaps.
Integrity: Data consistently structured, adhering strictly to recognised standards.
Auditability: Complete traceability of historical data records.
4. Relevance
Data provided closely matches user needs and expectations.
Fitness: Flexible and customisable datasets aligning closely with client-specific themes and applications.
5. Presentation Quality
Ensures clarity and ease of understanding.
Readability: Clearly structured data presentation in globally recognised, standard formats.
Structure: Consistent, logical structuring of data facilitating intuitive navigation and comprehension.
Twelve Data’s stringent adherence to these data quality standards ensures our clients consistently receive reliable, timely, and actionable financial market data tailored explicitly to their operational needs. Our rigorous framework enables businesses to leverage data confidently, driving informed decisions and competitive advantages.