Services / Across systems

Data mapping and integration

Connect sources without hiding the transformation logic.

We align source and target structures, define transformations and design refresh workflows so information can move between files, APIs, databases and partners with fewer surprises

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Clear mappings · Documented transformations

Map

Make fields, values, keys, rules and target structures explicit

Transform

Define how names, formats, hierarchies and calculations change

Refresh

Design repeatable hand-offs, checks, ownership and failure paths

The problem

Integration fails when the hand-off is treated as a black box.

Different systems can describe the same product, customer, location or transaction in different ways. A working connection needs more than moving columns: it needs agreed keys, value rules, transformations, refresh timing and a way to explain what happened when the output is not as expected.

We make those decisions visible and design an integration workflow that fits the real sources, tools and people involved

01 / Align

What is the source and target?

Define structures, keys, ownership, timing and expected outputs

02 / Transform

How does one representation become another?

Document mappings, calculations, reference data and exceptions

03 / Operate

What happens on every refresh?

Set checks, hand-offs, failure paths, alerts and maintenance responsibilities

Typical inputs and outputs

An integration design the team can run and explain.

The result can support a recurring file process, a reporting dataset, a partner exchange or a larger technical implementation

Source-to-target map

Fields, keys, formats, allowed values, required logic and ownership

Transformation rules

Standardization, joins, calculations, reference-data alignment and exception handling

Refresh workflow

Inputs, frequency, sequencing, validation checks, hand-offs and failure paths

Integration documentation

Assumptions, boundaries, open questions, test cases and maintenance guidance

Tools and system boundaries

Design the flow around the systems that actually exist.

Sources may include Excel or CSV files, partner templates, APIs, databases or exports from business systems. We can define the integration logic and operating model without prescribing a specific vendor or claiming to replace the organization’s engineering function.

Related thinking

AI is only as useful as the hand-offs around it.

A case study exploring how controlled data flows and workflow design support AI integration in FMCG

View the case

Need to connect sources without losing control of the logic?

Discuss the integration