The same job, customer or asset has several identities
Records do not match reliably across systems, so people fall back on manual searches, local knowledge and increasingly fragile join rules.
Operational data and reporting
When two systems disagree, find out why.
Strataflow traces records back to their source, preserves the exceptions and builds reporting that an operations team can explain in a meeting.
Common signs
The report is late because the data has to be repaired before anybody trusts it.
Two systems give different answers, and both look plausible
Definitions and timestamps differ, and nobody has agreed which source to trust. Every review begins with another reconciliation exercise.
A polished dashboard hides the data problem underneath
The charts look finished, but nobody can explain the baseline, the calculation, the missing records or what counts as an exception.
What the job may need
Use the skills the problem needs. Leave the rest out.
Operations and systems leaders whose records, forecasts or reports disagree often enough to cause rework, poor decisions or audit risk.
Capabilities
- Data inventory and trusted-source decisions
- Matching, normalisation and deduplication rules
- PostgreSQL/PostGIS models and migrations
- API and cross-system reconciliation
- Forecast, cost and KPI definitions
- Dashboards, audit history and exception reporting
Intended outcomes
- One agreed answer, with the source behind it
- Missing and conflicting records stay visible
- People can explain how every important number is calculated
- The report runs again without another month of manual repair
Prices and next steps
Agree the problem before committing to the fix.
Operational Data Review
From £750 + VATFive working days for one dataset or report
Take one disagreement back to the records behind it. Find where the answers diverge, agree what should be trusted and define the smallest correction worth making.
- A map of the sources and data flow
- A worked reconciliation sample
- Agreed KPI definitions and source findings
- A recommended fix with acceptance thresholds
Data Quality & Reporting Sprint
From £3,500 + VATTwo to four weeks for one clearly defined data flow
Build the matching, validation, audit trail and reporting needed for the agreed records and business rules. Migration is included where the fix requires it.
Reporting Improvement Partner
Scoped after the first data flow is liveKeep definitions current, watch the exceptions and extend the reporting without letting it drift away from the operation it is meant to describe.
Book a 20-minute callOperational data / portfolio prototype
SIREN shows where records fail to join and sources disagree.
The diagnostic interface shows match quality, missing identifiers, the source behind each answer and any remaining uncertainty. It does not pretend the data is more certain than it is.
See how it works
Strong fit
A good fit when...
- The disagreement can be narrowed to named systems or records
- A business owner can define what a correct result means
- Representative data can be reviewed through an agreed, secure route
- The organisation is willing to keep exceptions visible rather than force false certainty
Outside scope
Not the right route when...
- Open-ended cleansing of unknown data volumes
- Generic data-science experimentation without an operational decision
- Reporting whose definitions have no accountable owner
- Migration programmes without source and acceptance controls
Before you call
Questions people usually ask first.
Is this data cleansing?
It can include cleansing, but cleaning the current file is only half the job. We also decide which source to trust, how records should match, what happens to exceptions and how to stop the same problem returning.
Can you work with spatial data?
Yes. PostgreSQL/PostGIS, GIS records, UPRNs, routes, assets and spatial joins are a particular strength, especially when field and network systems need to agree.
Will you build the dashboard too?
Where it helps, yes. The dashboard comes after the definitions, quality thresholds and exception rules are agreed. It should show the answer, not disguise an unresolved data problem.
Operational data and reporting
Bring the two reports that should agree but do not.
Send a representative sample. That is usually enough to find whether the problem sits in the records, the matching rules, the process or the report itself.
Book a 20-minute call