Owner / CEO
Can we trust our numbers?
- I compare what leadership and operations need with where the numbers come from and how they are produced.
- I review metric definitions, data sources, manual adjustments, and ownership.
Data audit for business owners, CEOs, COOs, and CTOs
Find out whether you can trust your numbers, where you are overspending, and what needs fixing before you invest in another tool or AI. When every report tells a different story, leadership loses more than time—it loses confidence in its decisions.
The first 30 minutes will help us determine whether an audit makes sense, with no commitment. Then I propose a scope, timing, and price—or tell you that you do not need an audit right now.
I am Radek Duha, and I lead the audit personally.
For more than ten years, I have connected data, technology, and business decisions. I am here to understand what your business needs to know, how the numbers are actually produced, and what your current setup costs, rather than sell you another tool. The recommendations have to make sense technically, operationally, and financially.
- 10+ yearsin data, BI, and product technology
- An independent perspectivewithout selling a particular platform
When data becomes another source of uncertainty.
- The numbers disagree Meetings end with a debate over which report to trust.
- Reporting takes too much time Your team keeps tracking down data, joining it manually, or explaining it all over again.
- Costs rise without a clear return Licenses, infrastructure, and maintenance keep growing, but decisions are no easier.
- You are planning another investment Before investing in new BI tools, a data platform, or AI, you want to check that the foundations are sound.
Each role needs a different answer from the audit.
The audit brings leadership confidence, operational impact, technical condition, and real costs into one picture. Everyone can make decisions from the same understanding of what is happening.
COO / finance
Are we getting enough value for what we spend?
- I assess licenses, BI tools, the database, and ETL/ELT processes against how they are actually used.
- I identify costs hidden in manual work, unnecessary complexity, and dependence on one person or vendor.
CTO / data lead
What should we fix before adding another tool or AI?
- I check whether AI has the right data, definitions, permissions, and human oversight.
- I separate opportunities for a small test from problems that need stronger foundations first.
I know fast growth and the day-to-day reality of established products.
I have worked with data and reporting in companies where teams, technology, and leadership questions keep changing. That experience is why I do not look for a one-size-fits-all solution.
These logos indicate experience in these companies, not their endorsement of the audit.
An answer leadership can act on.
The findings connect business needs, operational reality, and the technical setup so you can make a decision.
The audit may also confirm that your current setup is sufficient and there is no reason to change it right now.
I do not sell licenses or a particular platform. The audit is not a disguised pitch for a new dashboard, and it does not have to mean replacing your team or vendor.
- An executive assessment
- A concise answer to the question behind the audit: what is working, what poses a risk, and why.
- A map of the current setup
- How leadership needs, data sources, metrics, reports, manual steps, costs, and responsibilities fit together.
- Priorities for what comes next
- What to keep, fix, simplify, stop, or validate with a small test, ordered by value and effort.
The audit starts before the platform decision.
Tableau, Power BI, Lightdash, dbt, and Keboola are tools. What matters is whether your current stack gives you the right numbers at a reasonable cost, without unnecessary manual work.
- Tableau
- Power BI
- GoodData
- Qlik
- Metabase
- Lightdash
- Apache Superset
- Google Data Studio
- dbt
- Keboola
Reporting, BI, data transformation, and controlled scripts as needed. If you are looking at data readiness for AI, read From ETL to AI agents.
Minimal disruption. Clear findings.
First, we clarify the decision. Then I check only what we need to support it.
- 01
The decision and the scope
In a 30-minute conversation, you explain what you need to decide. I propose the audit scope, the people involved, timing, and price.
- 02
Check what is actually happening
I start with conversations and available documentation. I access systems only where we need to investigate a specific question.
- 03
Findings for leadership
I deliver the findings, supporting evidence, and priorities. Together, we review what to keep, what to change, and what to leave alone for now.
Practical questions.
You will know the scope, people involved, access requirements, timing, and price before we start.
What will we agree on before starting?
The audit goal and scope, the people involved, the materials or access needed, the deliverable, timing, price, and any follow-up work that would be a separate engagement. We start only when we have a shared understanding of all of these.
How will we handle nonpublic data?
Before working with nonpublic data, we will agree in writing on which sources may be used, where they may be processed, who has access, and whether external AI tools are allowed. I do not work with nonpublic data without that agreement.
How much does an audit cost, and how long does it take?
The price and duration depend on the decision the audit needs to support and the number of people and systems we need to review. After the initial conversation, you receive a proposal covering scope, schedule, and price. We do not start until you know what you will get and when.
Does an audit mean replacing our team or vendor?
No. The audit gives you a second pair of eyes and evidence for your decision. It may confirm that your current setup makes sense, recommend targeted changes, or show what needs a different approach. I work with your existing team or vendor as needed.
Do you need access to all our systems?
No. We start with conversations and available documentation. If we need to investigate a specific question in a system, we agree on the purpose, scope, and a safe way to access it first. Blanket access to all your data is not a requirement.
What happens after you deliver the findings?
The engagement can end with the recommendations. If you want help with a workshop, project leadership, or implementation, we agree on that separately. Further work is optional.
Before you spend more on data, find out what actually needs attention.
Tell me what your business is working through. I will get back to you so we can discuss whether an audit makes sense and what it should cover.
Prefer email? jsem@radekduha.cz