Data lake platform
Darya is Niadad's data lake platform that ingests, stores, catalogues and governs enterprise data for analytics and AI.
- Data
- Niadad
- In development
Problem
Enterprise data is scattered across dozens of systems, files and sensors, and every analysis begins with a fresh manual extract. Without one governed home with a catalogue, quality rules and access control, reports disagree and AI models have no reliable data to learn from.
Platform overview
Darya is Niadad's data lake: it collects data from transactional systems, files, APIs and event streams, keeps it in raw, refined and curated layers, and exposes it to analysts and models with a catalogue, access policies and lineage. Binesh and Rayon work directly on top of it.
Key capabilities
Batch and streaming ingestion
Loads data from databases, files, APIs and streams (via Jarian) with ready-made connectors.
Layered storage
Keeps raw, refined and curated data in open, columnar formats with versioning.
Catalogue and lineage
Every dataset is searchable with its description, owner, classification and lineage.
Data quality
Runs validation and quality checks on pipelines and reports deviations.
Access control and masking
Enforces table-, column- and row-level access with policies and masking of sensitive data.
Analytical access
Available to Binesh, Rayon and analytical tools through SQL, notebooks and APIs.
Architecture
Ingestion layer with connectors and CDC
Object storage with open table formats
Processing engine and transformation pipelines
Catalogue, metadata and lineage
Access-policy and masking layer
Query engine and access APIs
Integrations
Use cases
Related platforms
Related insights
Let's build together.
If your organisation, bank or industry is ready to turn data into decisions, start the conversation here.