DATA PLATFORM SERVICES
Enterprise data platforms for analytics and AI
We design, build and operate data platforms with ingestion, processing, governance and serving designed together around your workloads.
- Governance and serving designed in from the start, not retrofitted later
- A managed lakehouse core on open table formats, so your data is never locked in
- Build vs buy decided deliberately, layer by layer, not by default
We design in layers, each with a clear responsibility.
So the platform stays comprehensible and every component can evolve independently. The layering matters: governance and serving are designed in from the start, not retrofitted after the data is already sprawling. That is the difference between a platform and a collection of pipelines. This is the platform track of Infrastructure and Platforms, the base for Data Engineering and everything above it.
Governance and serving are built in from the start, not retrofitted, which is exactly what keeps the platform comprehensible as it grows.
A platform, not a collection of pipelines.
What our data platforms include.
- Platform architecture designed across all layers, sized for your workloads and growth.
- A landing zone and foundation: security, networking, and governance baseline.
- Ingestion, storage, and processing stood up on your chosen platform.
- Governance and serving layers built in from the start, not retrofitted.
- Operations: orchestration, monitoring, and data FinOps cost controls.
- A deliberate build vs buy decision per layer, so nothing is custom by default or bought by habit.
Build the foundation, then prove a workload.
Architect
The target platform against workloads, scale, and constraints.
Decide
Build vs buy per layer, deliberately, not by default.
Foundation-first
Landing zone, security, and governance baseline before any workloads land.
Build
Ingestion, processing, governance, and serving as one coherent system.
Operate or transfer
With dedicated teams or a center of excellence owning it long term.
A managed lakehouse core on open formats, so you keep your leverage.
Our default bias is a managed lakehouse core on open table formats, for operational leverage without locking your data behind a proprietary format. The right answer depends on your team, scale, and constraints.
Build vs buy is decided layer by layer. A managed lakehouse core plus open formats usually wins, but portability, scale, and team maturity can shift the answer. See the Open Data Lakehouse foundation.
From sprawling point tools to one governed foundation.
Challenge: Product, inventory, and warehouse data sat across Stibo, MSSQL, and point tools with governance bolted on afterwards, so every new workload meant another rebuild.
Result: One layered cloud data platform unifying hundreds of thousands of SKUs, with real-time operational visibility, AI-driven data quality, and self-service BI for every team. Read the story.
What the platform enables, and what shapes it.
Open Data Lakehouse
The open table-format core the platform is built on, without vendor lock-in.
Agentic Data Foundation
The serving and vector layers that make the platform ready for agents.
Data Engineering
The pipelines and models that run on the platform once it is stood up.
Data Streaming and Real-Time Analytics
The event backbone the platform hosts for sub-second decisions.
Infrastructure and Platforms
The parent practice this platform capability belongs to.
Data and Analytics
The wider capability that turns data into decisions across the business.
What data leaders ask us first.
Most enterprises are best served by a lakehouse core that handles BI, ML, and streaming on open formats. Where a pure warehouse already serves reporting well, we integrate rather than replace.
Layer by layer. A managed lakehouse core plus open formats usually wins, but portability, scale, and team maturity can shift the answer. We make the trade-offs explicit before deciding.
Yes. We architect on Databricks, Snowflake, BigQuery, or your current stack, keeping what is sound and fixing what limits growth.
Architect and build a data platform that is governed, scalable, and AI-ready from day one.
A layered lakehouse on open formats, governance designed in from the start, and a deliberate build vs buy call at every layer.