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Data Quality & Observability

Detect anomalies in your flows before the business feels them. 53% of organisations have already deployed data observability, 31% more within the year.

Why clients call us

Data observability moved from comfort to necessity in about two years. Around 53% of organisations have already deployed it and a further 31% intend to within 12 months, an adoption curve steeper than neighbouring categories and driven by one recurring experience: the business noticing a broken pipeline before IT does.

Our angle is specific. Most tooling watches the warehouse. We instrument the movement, inside ACE, MQ, Sterling and the transformation layer, where volume drops, format drift and silent truncation actually originate. Freshness, completeness and conformity get measured where they break.

What we do

  • Flow instrumentationTechnical and business probes on the integration layer: message counts, latency, freshness, rejection rates, and a breakdown per partner.
  • Quality rules and profilingConformity, completeness, uniqueness and referential rules defined with the business and executed on the flow rather than after the fact.
  • Anomaly detection and alertingThreshold and pattern detection on flow behaviour, with alert routing that reaches someone who can act, and Watson AI where pattern detection earns its place.
  • Lineage and impact analysisField-level traceability from source to consumer, so an incident becomes a bounded impact statement instead of an investigation.
  • Pipeline health reportingOne shared view of pipeline health for IT, business owners and second-line functions. The same numbers, one source.
Freshness is the variable most people forget when they judge AI output. A model reading yesterday's positions gives yesterday's answer with today's confidence.

Buying triggers

  • An incident that reached the business before IT
  • Recurring disputes about whose numbers are right
  • Preparation of an AI or analytics programme
  • Service levels promised to partners with no measurement
  • An operational resilience requirement under DORA

Technical foundation

  • Instrumentation of ACE, MQ and Sterling flows
  • Custom probes and metrics exposition
  • Alerting and escalation chains
  • Power BI and Qlik health dashboards
  • IBM Watson AI for pattern detection
  • Microsoft Purview for cataloguing

Start here

A 5 to 15 day assessment gives you a map of this scope, a gap analysis and a costed plan.

Book an assessment

Market vocabulary

How this offer is named in tenders and job specifications

  • data observability
  • data lineage
  • anomaly detection
  • pipeline health
  • data freshness
  • data quality rules
  • SLA monitoring

Proof

Where this has already been delivered

Transport and supply chain

Round-the-clock monitoring on a full ESB platform

For a major European logistics player, an ESB platform integrating WMS, TMS, ERP and B2B partner flows, monitored and alerted around the clock on the flows the business depends on.

ESB · ACE · MQ · B2B · API · Monitoring

How we work on this

Assessment — 5 to 15 days, fixed price. Flow cartography, gap analysis, costed plan. A short document written to be signed by a decision-maker.

Build — A bounded project. Design, development, testing and cut-over on a defined perimeter.

Run — Recurring. Operations, monitoring, evolution and on-call cover on your critical flows.

Discuss your scope

Let's start with what actually flows today.

A 5 to 15 day assessment gives you a flow map, a gap analysis and a costed plan. Short, fixed price, written to be signed by a decision-maker.

Book an assessment