Data Audit
Know what data you have before you invest in data
A survey of your sources, your data quality and your current architecture, with a clear diagnosis and a prioritized roadmap. The starting point for any data or AI initiative.
Diagnosis + prioritized roadmap
The problem
- Nobody has the full map: data is scattered across databases, SaaS tools, spreadsheets and manual processes.
- Every team reports different numbers and there is no single source of truth.
- You want to do analytics or AI, but you don't know whether your data can support it.
- You already invested in data tooling and you still don't get business answers.
What's included
- Inventory of sources: databases, SaaS, events, files and manual processes.
- Data quality assessment: completeness, consistency, duplicates and freshness.
- Review of your current architecture (ingestion, storage, transformation, consumption).
- Governance diagnosis: ownership, access, catalog and traceability.
- AI-readiness assessment: what's missing before you can train or feed models.
- Roadmap prioritized by business impact and effort, with AWS cost estimates.
A diagnosis that ends in decisions, not in a PDF
The deliverable isn't a report to file away: it's a roadmap with prioritized initiatives, dependencies and cost estimates, ready to take to your committee. If you decide to execute it with us, the audit is already the first sprint.
How we work
Discovery
We interview business and IT to understand which questions can't be answered today, and why.
Plan & Quote
We define the scope of the survey (sources, domains and depth) at a closed price.
Execution
We survey sources, profile data and assess the architecture, documenting findings as we go.
Hand-off
We present the diagnosis, the prioritized roadmap and the quick wins you can tackle right away.
Stack & technologies
The full map of your data, in weeks
FAQ
How long does a data audit take?
It depends on the number of sources and domains, but most are done in a few weeks. We lock scope and timeline during discovery.
Does everything need to be on AWS already?
No. We survey whatever you have, on-premise, on another cloud or in SaaS. The roadmap does take you toward a data architecture on AWS.
What do I get at the end?
A source inventory, a quality and governance diagnosis, an AI-readiness assessment and a prioritized roadmap with cost estimates.
Is it useful if my real goal is AI?
Especially. Most AI projects stall on data, not on the model. The audit tells you what to fix before you invest.
