ASTRIVERA DataLake is independently developed data infrastructure for collecting, processing, governing, storing and publishing large volumes of historical and incremental data across markets and providers. It establishes data assets with consistent standards, defined quality requirements and recorded provenance.
A unified ingestion and processing architecture standardises data from different providers. Instrument identity, trading calendars, time conventions, corporate actions, historical coverage and revisions are managed under consistent data semantics, enabling datasets from different sources and periods to be processed and associated according to explicit rules.
Built-in data quality management checks completeness, consistency, duplicate records, missing intervals and anomalous values. Assessments also consider data sources, publication timing and historical coverage. Raw records, processed data and validation evidence are retained separately so that data quality can be reviewed and verified over time.
Data asset management extends from initial collection to controlled publication. Raw inputs, standardised datasets, derived outputs and published releases are maintained separately. Catalogues, version identifiers and lineage records preserve traceability from original inputs to final data products. Updates, corrections and republications retain their version relationships, allowing existing research to continue referring to the precise data on which it was based.
The platform supports data discovery, coverage analysis, version selection and controlled publication. Research and analytical workloads can select resources by market, time period, data type and suitability requirements, establishing a reliable data foundation for strategy development, model training, backtesting and other authorised uses.
DataLake combines independent deployment and local processing with controlled connections to external data providers. Automated task management supports continuous collection, incremental updates, validation and publishing. Monitoring, storage management, migration and recovery maintain data integrity, consistency and availability across supported computing and storage environments.
Cross-platform deployment. Supports macOS, Windows and Linux, with independent operation on professional workstations and in institutional private environments. Data storage, computing resources and controlled access can be configured to meet deployment requirements.
Core Capabilities
- Multi-Market and Multi-Provider Data Ingestion
- Large-Scale Historical and Incremental Data Management
- Data Standardisation and Quality Governance
- Instrument Identity and Time Semantics
- Data Catalogue and Coverage Analysis
- Provenance and Lineage
- Separation of Raw and Derived Data
- Versioned Data Publishing
- Automated Operations and Task Recovery
- Local Storage and Cross-Platform Deployment