Data & Analytics Maturity Assessment
Find out whether your data can support the decisions your business is already making with it —before you build anything else on top. We assess data quality, lineage and governance, the architecture that moves it, and your team's analytics capability.
Companies invest in BI tools and predictive models on top of data nobody certified: metrics that don't reconcile across departments, indicators that change depending on who calculates them, and a team that no longer trusts the report. This assessment separates the data problem from the tooling problem.
Don't decide on unverified data
If the same metric differs across two departments, the dashboard isn't the issue. We diagnose quality, lineage and definitions before your committee decides on them.
Organize by domain, not by tool
Switching platforms won't fix an ownerless data model. We prioritize by business domain, each with an owner and a single definition.
Actually enable AI
No agent or predictive model outperforms the quality of your data. This assessment is the real prerequisite for any AI initiative.
Data degrades on its own.
Every new integration, every added field and every staff change shifts data quality and governance. Measuring maturity annually keeps data a governed asset instead of debt that grows quietly.
Measure progress
Compare maturity by domain year over year and prove advancement with evidence, not perceptions.
Industry benchmark
Know where you stand against peers and what level of governance your sector and regulator expect.
Re-prioritize domains
Address the domains currently blocking decisions and release the ones already stable.
What you gain from the assessment.
A real data inventory
What data you hold, where it lives, who produces it and who consumes it —including what nobody currently claims.
Measurable trust
Quality and lineage scored by domain, so you know what you can decide on and what you can't yet.
Architecture with rationale
A target model for ingestion, storage and consumption that coexists with your core —no rip & replace.
Governance that doesn't block
Roles, single definitions and access controls that enable self-service instead of obstructing it.
A foundation ready for AI
The data requirements of every AI use case you have in mind, made explicit and prioritized.
Cost under control
Where you're paying for storage and processing nobody queries, quantified.
From scattered data to a decision you can trust.
Diagnosis by domain
Maturity level across quality, lineage, governance and accessibility, domain by domain.
Target architecture
The data model and analytics platform your operation needs, with the gaps against today.
Remediation roadmap
Initiatives ordered by decision impact and effort, with quick wins identified.
What you receive at the end.
- Data maturity report by domain (quality, lineage, governance, accessibility).
- Inventory of sources, flows and consumers, with owners identified.
- Quality gap map, with the impact on decisions that depend on it today.
- Target data architecture and analytics platform model.
- Data requirements for each prioritized AI use case.
- Remediation roadmap prioritized by impact and effort.
- Governance model: roles, single definitions and access policy.
- Executive presentation for your committee.
About the Data & Analytics Maturity Assessment.
What exactly do you assess?+
How is this different from a BI project?+
Do I need a data warehouse or lakehouse already?+
Is it useful if my real goal is adopting AI?+
How long does it take?+
How do I start?+
Decide on data you can trust.
Book your Data & Analytics Maturity Assessment: you'll know which data is ready, what needs fixing and in what order —before you build on top of it.
Book my assessment →