The same job, customer or asset has several identities
Records cannot be matched reliably across systems, so teams rely on manual lookup, local knowledge and increasingly fragile join rules.
Operational data and reporting
Make your operational data trustworthy.
Strataflow reconciles disconnected systems, repairs the rules behind unreliable records and builds reporting that operations teams can explain and act on.
Recognisable symptoms
The report is late because the data has to be repaired before anybody trusts it.
Two systems produce two defensible answers
Definitions, timestamps and source authority are unclear, making every operational review a reconciliation exercise.
A dashboard hides the quality problem underneath it
The presentation looks finished, but nobody can explain the baseline, calculation, missing records or exception threshold behind the KPI.
What Strataflow can deliver
Practical capability tied to a controlled outcome.
Operations and systems leaders whose records, forecasts or reports disagree often enough to create rework, weak decisions or audit risk.
Capabilities
- Data inventory and source-authority design
- 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 explainable operational source of truth
- Visible exceptions instead of silently discarded records
- Reports with agreed definitions and calculation basis
- A repeatable data flow that does not depend on manual repair
Commercial route
Buy clarity first. Build only when the boundary is credible.
Operational Data Review
From £750 + VATFive working days for a bounded dataset or report
Map the sources, sample the disagreement, identify quality and authority risks, and define the smallest useful correction.
- Source and data-flow inventory
- Reconciliation and quality sample
- KPI and authority findings
- Implementation recommendation and acceptance thresholds
Data Quality & Reporting Sprint
From £3,500 + VATTwo to four weeks for one bounded flow
Implement the matching, migration, validation, audit and reporting layer for named systems, records and business rules.
Reporting Improvement Partner
Scoped after the first data flow is liveMaintain definitions, monitor exceptions and extend decision support without allowing the reporting layer to drift from operations.
Discuss commercial fitOperational data / portfolio prototype
SIREN makes missing joins and source conflicts visible.
The diagnostic interface exposes match quality, missing identifiers, source authority and uncertainty rather than presenting an unjustified answer.
Inspect the evidence
Strong fit
Use this route when...
- The disagreement can be bounded to named systems or records
- A business owner can define what a correct result means
- Representative data can be reviewed through an agreed handling route
- The organisation is willing to preserve exceptions rather than force false certainty
Outside scope
Not the right route for...
- 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
Questions before a fit call
Enough detail to decide whether this is your route.
Is this data cleansing?
Cleansing may be one deliverable, but the service is broader. It establishes source authority, matching rules, exceptions, definitions and a repeatable flow so the same quality problem does not simply return.
Can you work with spatial data?
Yes. PostgreSQL/PostGIS, GIS records, UPRNs, routes, assets and spatial joins are a strong part of the portfolio, especially where field and network systems need to be reconciled.
Will you build the dashboard too?
Where useful, yes. The reporting interface follows agreed definitions, quality thresholds and exception handling rather than being treated as a separate presentation exercise.
Operational data and reporting
Bring the two reports that should agree but do not.
A representative sample is enough to decide whether the issue is matching, source authority, process discipline or the reporting logic itself.
Book a 20-minute fit call