A fixed-scope audit of your marketing data infrastructure: pipeline reliability, modeling quality, reporting cost, and a prioritized remediation roadmap.
Nobody can say how bad it actually is
Teams know something is wrong with their data. Reporting is late, numbers get questioned, and every new request takes weeks. What nobody can state precisely is where the failure is: whether it is ingestion, modeling, the BI layer, or process. So remediation gets guessed at, often by buying a tool that addresses a symptom. Meanwhile the risks that matter, such as a single undocumented pipeline one person understands, stay invisible until that person leaves.
What the audit covers
- A full inventory of pipelines, sources, transformations, and reporting surfaces, including the undocumented ones
- Reliability assessment: what fails, how often, how it is detected, and how long it takes to notice
- Data quality and modeling review, including whether key metrics are defined consistently
- Cost review across warehouse compute, connector licensing, and analyst hours spent on manual work
- Key-person and documentation risk: what breaks if a specific individual is unavailable
- A prioritized roadmap with effort estimates, sequenced by impact and dependency
How we work
Interview the people who actually run and consume the data, not only the sponsor
Get read access to the warehouse, orchestration, and repos, and inspect the real state
Trace two or three important metrics from source to dashboard and find where they diverge
Present findings, take challenge from your team, and deliver the final written roadmap
Typical stack
Frequently asked questions
Read-only access to the warehouse, orchestration tool, and transformation repo, plus time with two or three people who work with the data daily. We can work from documentation and interviews alone if access is genuinely blocked, but the findings will be weaker and we will say so.
Usually, for two reasons. First, the audit turns known problems into a prioritized, costed sequence, which is what unlocks budget. Second, it consistently surfaces things nobody knew, most often silent data quality issues and single points of failure.
A written report covering current state, findings ranked by severity, and a sequenced roadmap with effort estimates, plus a working session to walk through it. It is written to be handed to your team or another vendor without translation.
A vendor assessment exists to justify a purchase and the conclusion is known before it starts. This can conclude that your stack is fine and the problem is process, which has been the outcome more than once.
Go deeper
Book a data audit
Tell us roughly what your stack looks like and we will scope the audit and what access it needs.
Start a project