Three systems, three revenue figures
For an agreed period, we reconcile definitions, posting dates, currencies and identifiers. The result distinguishes differences with a business explanation from issues that need correction.
DATA SCIENCE / 01
Data quality & foundations
Know what you can build on.
Figures from your ERP, CRM and spreadsheets disagree? We examine an agreed slice of your data, make errors and gaps visible, and develop repeatable preparation steps. Your next analysis starts with a foundation everyone understands.
IN PRACTICE
A question from your working day.
For teams preparing a migration, dashboard or forecasting project, and for business teams that need to explain conflicting figures.
A dependable migration starting point
Before a move, we check selected tables for duplicates, missing required values and broken relationships. Ambiguous cases go to the responsible people with the context needed for a decision.
CONCRETE DELIVERABLES
What we agree to deliver.
We specify the extent of these deliverables in your proposal, together with verifiable acceptance criteria.
- Source inventory & definitions
- Documented origin, ownership and update schedules for agreed sources, with a data dictionary for the fields and measures that matter.
- Quality profile & validation rules
- An assessment of completeness, uniqueness, consistency and freshness. Repeatable tests distinguish errors, warnings and valid business exceptions.
- Preparation & action plan
- Versioned transformations for the agreed dataset, a traceable issue list and prioritised corrections to source data and data flows.
BEFORE WE START
A scope both sides can work with.
What we need from you
- A concrete business question, identified data sources and a business owner who can resolve ambiguities.
- Authorised access to an agreed extract, with sensitive fields removed or pseudonymised where possible.
- Agreed rules for purpose, retention, access and deletion of project data.
What needs a separate agreement
- This does not cover all company data by default. Sources, fields, data volume and time period are specified in the proposal.
- Your responsible team decides ambiguous business mappings. Source systems are changed only within the agreed scope.
- A full migration, additional integrations and ongoing quality monitoring are separate services.
STEP BY STEP
Reviewable progress. Clear decisions.
Define the question & dataset
We identify sources, access permissions, quality goals and the criteria you will use to accept the result.
Review the data profile together
We examine a representative extract. Findings are checked against business knowledge before becoming correction rules.
Implement & verify the rules
Transformations and tests run reproducibly. Before-and-after comparisons and spot checks show improvements and unresolved errors.
Hand over with clear ownership
Your team receives the results, instructions and a guided walkthrough. Every open issue has an owner and a next step.
YOUR TEAM TAKES OVER
The handover is part of the project.
We agree ownership, access and usage rights at the start, including the conditions of third-party components.
- A data dictionary, source lineage and documented quality findings.
- Source code for the agreed preparation steps and tests, with rerun instructions.
- A decision log, known limitations and a walkthrough for the responsible team.
A SCOPED PROJECT / PRICE ON REQUEST
Start with one concrete question.
Describe the decision, your available sources and who will use the result. We clarify feasibility and propose deliverables, acceptance criteria, schedule and price. Each further stage is agreed explicitly.
A short description is enough for the first enquiry. Please do not send confidential datasets or access credentials through the contact form.
Request a project proposalView shop scope (German)
Project work and ongoing costs are shown separately. Hosting, licences, compute and support are included only when explicitly agreed.