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Data Engineering

Connected, checked data, there when you need it.

The problem

The data exists, but it moves by hand.

  1. Every week someone copies extracts from one system into another.

  2. When a flow breaks, you find out from a wrong report.

  3. Each system names the same customer, item or supplier differently.

Our contribution

Data integration means reconciling differences in structure, timing and meaning across systems. We examine sources, access methods and dependencies, then define how to capture new records, updates and deletions. Each flow has explicit expectations for fields, keys, refresh frequency and destination. ERP systems, production systems, applications and files are connected while keeping the origin of each data item and its transformation path recognisable through to its intended use.

We design repeatable loading processes: rerunning a step needs defined behaviour that avoids duplicating records or losing updates. Structure, completeness and consistency checks distinguish usable data from exceptions that need investigation. Orchestration, execution records and recovery procedures help explain where a process stopped and which information is affected. The design accounts for access restrictions, available processing windows and operating responsibilities agreed with the team, including how source changes are identified and handled.

What the work covers

  1. Ingestion and updates

    We choose full or incremental extraction to suit the source, defining keys, change handling and loading windows.

  2. Quality and exceptions

    We check fields and relationships, retaining exceptions and the context needed to understand and correct them.

  3. Orchestration and recovery

    We specify dependencies, retries and restart points so an interruption can be handled without indiscriminately rerunning the entire flow.

  4. Transformation lineage

    We connect sources, processing steps and destinations through metadata and records that help assess errors and the impact of changes.

What takes shape

Practical work products, scoped to the engagement.

  1. The problem
  2. The analysis
  3. The result
#Work productWhat it contains
01Integration flowsIngestion and transformation processes implemented within the agreed scope, with documented configuration and dependencies.
02Execution checksChecks on loading and data quality, with evidence of exceptions and criteria for handling them.
03Operating instructionsProcedures for running, checking and recovering flows, with defined responsibilities and intervention points.

Six stages

The assessment path

Understand how data moves between systems, where it gets lost and where it breaks, guided by DAMA-DMBOK practice.

A bounded engagement, with scope and fee agreed before work begins. If you go ahead with the project, the assessment fee is deducted from the follow-on engagement.

The six stages and the results they feed
#StageSource and flow mapSample quality and findingsInitial action plan
01Interviews with process owners and IT: which activities depend on which data flows.yesnono
02Inventory of sources and flows: systems, interfaces, manual extracts, schedules.yesnono
03Quality profiling on agreed samples: completeness, accuracy, consistency, timeliness.noyesno
04Operations review: orchestration, monitoring, error handling, access and security.noyesno
05Architecture and integration review: duplication, dependencies, fragile points.yesyesno
06Priorities and an initial action plan.noyesyes

What you receive

A
Source and flow map
B
Sample quality and findings
C
Initial action plan

Two ways to start.

01 · Free data check-up

Start with a data check-up.

About an hour online, a written summary within five working days. No cost, no obligation.

  1. 01RequestAsk for the check-up through the contact form.
  2. 02Online meetingAbout an hour to trace systems, sources, reports and weak points.
  3. 03Written summaryWithin five working days: current situation, issues and recommended path.
  1. The situation
  2. The issues
  3. The path

02 · Service assessment

Go straight to the assessment.

If you already know this service is the one, we start with the six stages below.

  1. 01Interviews with process owners and IT
  2. 02Inventory of sources and flows
  3. 03Quality profiling on agreed samples
  4. 04Operations review
  5. 05Architecture and integration review
  6. 06Priorities and an initial action plan
Request the Data Engineering assessment