luminovainfotech

Cloud & Data

Data Platforms

Lakehouse architectures designed for AI and analytics together

A modern data platform serves BI, ML, and AI workloads from one source of truth — without silos, copy chains, or governance debt. We design and build platforms that hold up under all three.

What we deliver

Data Platforms capabilities, end to end

Lakehouse foundation

Open-format lakehouse design that supports SQL, ML training, and streaming consumption from the same storage layer.

  • Iceberg / Delta / Hudi storage choice analysis
  • Compute engine separation: SQL, Spark, streaming
  • Catalog strategy: Unity, Polaris, Snowflake Horizon, AWS Glue
  • Cost-aware storage tiering and lifecycle

Semantic and metric layer

A versioned, governed semantic layer so AI agents, dashboards, and notebooks all answer questions the same way.

  • dbt Semantic Layer or LookML implementations
  • Metric definitions with ownership and tests
  • Self-service exposure to BI and AI consumers
  • Backward-compatibility and deprecation policies

Data products and mesh patterns

Where it fits, a data-products approach with clear ownership, SLAs, and consumer contracts.

  • Domain-aligned data product definitions
  • Producer / consumer contracts and SLAs
  • Discovery and self-service catalog patterns
  • Federated governance with central guardrails

ML and AI readiness

The platform features ML teams actually need: feature stores, vector indexes, and reproducible training data.

  • Feature store design (Databricks Feature Store, Feast)
  • Vector storage alongside warehouse and lakehouse
  • Reproducible training datasets with versioning
  • Model serving integrations

How we work with you

Engagement shapes

Three typical ways we engage on data platforms — adapted to your scope, timeline, and team.

4–6 weeks

Platform Strategy

Target architecture, tooling decisions, build plan.

12–20 weeks

Platform Build

Lakehouse, semantic layer, governance, and first set of consuming data products.

Ongoing

Platform Run Partner

Operate the platform alongside your team.

Tools & technologies

Built on what your teams already know

We work with industry-standard tooling and open standards — no proprietary lock-in.

Lakehouse platforms
DatabricksSnowflakeGoogle BigQueryMicrosoft Fabric
Catalogs
Unity CatalogSnowflake HorizonAWS GlueApache Polaris
Semantic layer
dbt Semantic LayerCubeLookML
Feature stores
Databricks Feature StoreFeastVertex AI Feature Store

Let's talk

Tell us what you're building.

Share the shape of your initiative and we'll respond within one business day with a tailored point of view — and the names of the senior people who would lead the work.

Opens in your email app — review and click Send.