One Architecture to Unify All Your Data — Structured, Unstructured, and Streaming
We design and build enterprise data lakehouses on Databricks Delta Lake and Microsoft Fabric OneLake — ingesting clinical records, ERP exports, IoT event streams, and EV telemetry feeds into a governed, versioned, AI-ready foundation. Eight data sources unified. One platform your teams can trust.
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Data lakes promised everything. Most delivered a swamp.
The original data lake vision was compelling: land all your data in one place, query it whenever you need it.
In practice, without schema enforcement, data quality layering, and unified governance, data lakes become ungovernable — expensive to maintain and impossible to trust.
The modern answer is the data lakehouse — combining the flexibility and scale of a lake with the structure and governance of a warehouse.
Built on Databricks Delta Lake or Microsoft Fabric OneLake, a properly architected lakehouse gives every team in your organization — analytics, AI/ML, clinical operations, manufacturing intelligence, and EV fleet management — access to data they can actually act on.
Bronze. Silver. Gold. A proven framework for data quality at enterprise scale.
Every data source lands here exactly as received — no transformation, no filtering. EHR ADT feeds, IoT sensor payloads, EV telematics from OEM APIs, ERP flat file exports, claims files, API event streams. This layer is the permanent, immutable record of what arrived and when.
Raw data is validated, deduplicated, standardized, and joined across sources. Business rules are applied. PHI is masked where required. IoT noise is filtered. This is the layer your data analysts and operational teams trust for ad-hoc queries, self-service reporting, and operational dashboards.
Aggregated, semantically rich, domain-specific datasets built for consumption. Power BI semantic models, ML feature stores, Copilot grounding data, and executive dashboards connect here. This is the data layer your business makes decisions on.
Databricks Delta Lake or Microsoft Fabric OneLake — we match the architecture to your workload.
Delta Lake brings ACID transactions, schema enforcement, time travel, and scalable metadata management to your data lake — making it production-grade and queryable without copying data into a separate warehouse.
- Multi-hop medallion pipelines (Bronze → Silver → Gold) on Azure
- Unity Catalog for fine-grained data governance, lineage, and access control across all assets
- Delta Live Tables for declarative, monitored pipeline development
- MLflow integration so ML teams build models directly on governed Gold-layer features
- Databricks SQL warehouses for business analyst self-service querying
- Structured Streaming on Delta Lake for near-real-time continuous ingestion from Event Hubs
OneLake is Microsoft's unified storage layer — one lake for your entire Fabric estate, eliminating data copies between services. Fabric Lakehouses sit on top of OneLake and interoperate natively with Power BI, Fabric Warehouses, Fabric Data Factory, and Azure ML.
- Fabric Lakehouses with OneLake as the single storage backbone
- Fabric Dataflows Gen2 and Data Pipelines for ingestion from EHR, ERP, and third-party systems
- Direct Lake mode for Power BI — real-time semantic queries without import duplication
- Microsoft Purview integration for data cataloging, lineage, and HIPAA/SOC 2 compliance governance
- Shortcuts to Azure Data Lake Storage Gen2 for hybrid lake architectures
Lakehouses we've architected across healthcare, manufacturing, and EV.
Unified clinical data from disparate EHR and ancillary systems into a governed lakehouse
A health system was operating with clinical data fragmented across their primary EHR, multiple ancillary systems, and departmental databases — with no common data layer for analytics or AI. Every analytical query required manual extracts and cross-system reconciliation.
We built a Microsoft Fabric Lakehouse that ingested data from all EHR and operational sources via Fabric Data Pipelines, normalized it through a Silver-layer transformation process aligned to FHIR standards, and surfaced Gold-layer datasets to Power BI for inpatient dashboards and to Azure ML for length-of-stay prediction models.
- FHIR-aligned data normalization in the Silver layer
- PHI masking and RBAC governance via Microsoft Purview
- Gold-layer feature store feeding length-of-stay and readmission prediction models
- Power BI Direct Lake mode for sub-second clinical dashboard queries
- 8 structured and unstructured data sources unified into a single governed Fabric Lakehouse.
- Reporting cycle reduced from 1 week to 4 hours.
- Clinical, financial, and operational teams working from one trusted data layer.
A lakehouse is only as valuable as the data you can trust inside it.
Unity Catalog
Fine-grained access control, data lineage, and asset discovery across all tables, notebooks, models, and pipelines in your Databricks environment. One governance layer for the entire lakehouse — not per-workspace policies stitched together.
Microsoft Purview
Automated data cataloging, lineage visualization, and sensitivity labeling across your Fabric Lakehouse and OneLake assets. Compliance controls for HIPAA, SOC 2, and GDPR baked into the data layer.
RBAC & Column-Level Security
Role-based and column-level access controls ensure PHI, financial data, and proprietary telemetry are only accessible to the right personas — enforced at the storage layer, not just the reporting layer.
Data Quality Rules at Every Layer
Automated data quality checks at Bronze ingestion, Silver transformation, and Gold aggregation — with alerting and lineage so your teams know exactly when, where, and why a data quality issue entered the pipeline.
What makes our lakehouse practice different
Nayaati accelerates manufacturing delivery by 3–4x
Industrial and manufacturing clients don't start from scratch. Nayaati's pre-built Delta Lake pipelines, semantic models, and IoT templates mean your equipment analytics go from kickoff to production in weeks.
Dual-platform expertise: Databricks + Microsoft Fabric
We architect on both — and we know when each is the right call. Databricks for teams running heavy ML, multi-cloud, or complex streaming workloads. Fabric for organizations standardizing on the Microsoft ecosystem. Most clients benefit from both working together.
Industry data models ready to deploy
We bring pre-built Silver-layer transformation logic and Gold-layer semantic models for healthcare (FHIR-aligned), manufacturing (equipment telemetry), and EV/energy (multi-OEM vehicle schema). Your implementation starts weeks ahead.
Continuum closes the AI governance loop
Once your lakehouse is live, Continuum — our AI governance platform — ensures every AI use case built on top of it is vetted, approved, and audited against your organization's policies before it goes to production.
Eight data sources. One governed lakehouse.
Four-hour reporting cycles.
Let's design your lakehouse architecture — and show you exactly what it takes to get from your current state to a governed, AI-ready data foundation.
Book a Discovery CallFAQs
Data Lake Solutions — FAQ
Answers to the questions data and architecture leaders ask before designing or migrating to an enterprise data lakehouse.