Services · Data Platforms
Every system holds a piece of the truth, every department keeps its own copies, and every leadership meeting starts with a debate about whose number is right. Splendor's data platform consulting builds the governed foundation underneath it all — one source of truth for reporting today, and the data foundation your AI ambitions actually require.
The Problem
Finance, operations, and sales each report a different number for the same thing.
"Active customer" means something different in every system that stores one.
Analysts spend most of their week assembling data instead of analyzing it.
Critical reporting runs on spreadsheet extracts that die when their owner leaves.
The AI initiative stalled the moment someone asked, "which data would it use?"
Sound familiar?
What We Do
We don't start with a product. We start with your business capabilities and the decisions each one needs data for — then define ownership, definitions, and quality rules, and build the governed platform domain by domain. The first trusted numbers land in a quarter; the foundation compounds from there.
How It Works
Data maturity is assessed in Discover and designed in Design — the platform is built and proven through the Splendor Transformation Framework.
Data maturity findings per capability — where the copies live, where definitions diverge, which decisions are starved.
Data strategy, domain model, governance operating model, and platform architecture — sequenced by business impact.
First governed domain live in a quarter; then domain after domain, with adoption and trust measured, until it's how the business runs.
Outcomes
Leadership meetings that start with the decision, not a debate about whose number is right.
Analysts analyzing instead of assembling — and answers available in hours, not at month-end.
Governed, defined, quality-checked data — the difference between AI in production and AI in perpetual pilot.
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FAQ
A platform where data from your operational systems lands with defined owners, agreed definitions, quality checks, and access controls — so every report, dashboard, and AI model reads the same trusted answer. Governance is what separates a data platform from a data swamp.
You need the foundation the AI will read from. Models trained or grounded on inconsistent, undefined, ungoverned data produce confident nonsense. Data strategy before AI strategy isn't a slogan — it's the order of operations that determines whether AI reaches production.
Because each report reads a different copy of the data, with a different definition of the same term — "active customer", "enrolled student", "open order". The fix is architectural: one system of record per domain, shared definitions leadership signs off on, and a platform every consumer reads from.
The first governed domain — one set of numbers leadership trusts — should land in a quarter, not a year. We build domain by domain, prioritized by business impact, so value ships while the platform grows.
The one that fits your estate, skills, and budget — we're deepest on the Azure data stack, and we name tools only after the strategy and architecture are set. The platform choice is a consequence of the design, never the starting point.
Once the foundation is trusted, business intelligence turns it into decisions — and our AI & Intelligent Automation practice builds on it.
Ready to move?
Bring the two reports that never match, or the AI initiative waiting on "the data problem." We'll show you what a governed foundation looks like — and which domain to build first.