Knowledge center · Architecture

How do you create reliable data flows?

Reliable data flows emerge when, for every important data set, it is clear which system maintains it as the system of record, how it reaches the other systems, and who is accountable for its quality. Add a binding definition for each KPI and reconciliation rules that surface discrepancies automatically. Data is then captured cleanly once and is available wherever it is needed.

Author Andreas O. Schwan, Managing PartnerLast reviewed

Legal information as of October 8, 2026. This article is not legal advice.

The cause

Why three reports show three numbers

When the monthly report shows three figures for the same revenue, the cause is rarely a calculation error. Usually the figures come from different systems, with different cut-off dates and different definitions, and each one is calculated correctly on its own terms. Customer data lives in the CRM, the ERP, and spreadsheets alongside them, each maintained slightly differently. That is a data architecture problem, not a people problem.

Typical break points

  • The same master data in several systems, with no system of record
  • KPIs defined differently in each department
  • Data copied and re-entered by hand
  • Interfaces nobody has documented
  • No traceable lineage from report to source

The approach

From the report back to the source system

The most reliable path to clean data flows starts at the end: with the KPIs that decisions are based on. From there, each figure is traced back to its source system, noting where it is copied, converted, or supplemented by hand. The result is a data map that can be read without a technical background and that forms the basis for the target architecture.

In the Business Data Transformation Framework, this approach belongs to the Understand and Architect phases: first the data map, then the target architecture.

Four steps, each with a result

  1. Step 1

    Capture sources

    Record systems, data sets, and interfaces, including the spreadsheets next to the systems.

  2. Step 2

    Trace flows

    Follow selected KPIs from the report back to the source system.

  3. Step 3

    Measure quality

    Make completeness, timeliness, and contradictions visible with metrics.

  4. Step 4

    Design the target

    Define systems of record, data flows, and accountability, and agree on them.

Target state

One system of record, one reliable flow

The target architecture defines which system is the system of record for which data, how data should flow, and who is accountable for its quality. Existing systems stay where they do their job. Only what is demonstrably redundant is switched off, and only after a period of parallel operation with reconciliations. The guiding vision is Zero Friction Data Flow: data is captured once and used reliably everywhere.

A clear data architecture is also the precondition for any sensible use of AI. A model is only as reliable as the data it works on. Fragmented system landscapes produce fragmented results.

Zero Friction Data Flow: what the guiding vision requires

Capture once
Each piece of information is recorded and maintained in exactly one place.
End to end
Data flows from the source system to the report without manual re-keying.
Reliable quality
Reconciliations and metrics expose discrepancies before they reach a report.
Under the company’s control
The company knows where its data resides and who can access it.
Traceable
The lineage of every figure is documented for audits and supervisors.

Questions from leadership

What executives ask about it

What is a system of record?

The system in which a data set is maintained as the authoritative version, for example the customer master in the CRM or the item master in the ERP. All other systems take the data from there and do not change it themselves. For each data domain there is exactly one system of record at any point in time.

How can you tell a good data architecture?

Meetings revolve around decisions rather than around which number is right. Every KPI has a defined source and calculation, errors are fixed where they arise, and the lineage of every number can be traced.

Does data architecture matter for BCBS 239 or DORA reviews?

Yes. BCBS 239 requires banks to aggregate their risk data traceably, and DORA requires financial entities to identify their ICT assets and their dependencies. Documented data lineage from report to source is key evidence for both.

As of October 2026 · not legal advice

What does Zero Friction Data Flow mean?

Zero Friction Data Flow is the guiding vision of SIMO GmbH for data architecture. Data is captured cleanly once, flows between systems without manual work, and is available wherever it is needed. The vision describes a target state against which every architecture decision can be measured. It is neither a piece of software nor a service of its own.

Author and sources

Who answers, and what it rests on

Sources and further reading

  1. Basel Committee on Banking Supervision: BCBS 239, Principles for effective risk data aggregation and risk reporting, 2013 (external site)
  2. Regulation (EU) 2022/2554 (DORA), Article 8 (external site)
  3. DAMA International: DAMA-DMBOK, Data Management Body of Knowledge, 2nd edition, 2017
  4. ISO 8000, Data quality (series of standards)
  5. SIMO GmbH: Glossar Datenstrategie, Eintrag Zero Friction Data Flow [in German], 2026

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