---
title: "Data Architecture: data flows, sources and ownership"
description: "Data architecture shows which data your company holds, where it originates, how it flows and who owns it. The foundation for reliable figures and for AI."
canonical: "https://simo-online.com/en/services/data-architecture"
---

# Data Architecture: data flows, sources and ownership

Data architecture shows which data your company holds, where it originates, how it flows and who owns it. The foundation for reliable figures and for AI.

Dargestellte Fassung: https://simo-online.com/en/services/data-architecture

## Data Architecture

Data architecture describes which data your company holds, where it originates, how it flows between systems and who is accountable for it. It turns scattered data stores into one coherent system that decisions and AI can rely on.

### Knowing where data originates and where it flows

- Almost every company has more data than clarity about it. Customer data sits in the CRM, in the ERP and in several spreadsheets, each maintained slightly differently. Key figures are calculated differently in different places. When the monthly report shows three numbers for the same revenue, the cause usually lies in the data architecture.
- We record your data landscape as it really is today: which systems produce which data, through which interfaces it is passed on, and where it is copied or maintained by hand. The result is a data map that can be read without technical background.
- On this basis we design the target architecture. It defines which system leads for which data, how data should flow and who is responsible for its quality. Existing systems stay wherever they do their job. Our guiding principle is Zero Friction Data Flow: data is captured cleanly once and is available wherever it is needed.
- 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.

### Reliable figures, without manual reconciliation

#### One number for every key figure

Every core key figure has a defined source and a defined calculation. Meetings revolve around decisions instead of the question which number is right.

#### Less manual work

The data map shows where data is copied, reconciled and patched by hand today. The target architecture tackles the causes and removes this work for good.

#### Clear ownership of data quality

Every data set has a leading system and an accountable person. Errors are fixed where they arise, not anew in every report.

#### Ready for analytics and AI

Clean data flows are the precondition for analytics and AI applications to deliver reliable results. Fragmented system landscapes deliver fragmented results.

- Data sources and systems
- Data flows and interfaces
- Master, transactional and reference data
- Data quality and data lineage
- Accountability for data (data owners)
- A data map of your company
- Target architecture for your data
- Reconciliation rules and data quality metrics

### Capture the sources

We record systems, data stores and interfaces, including the spreadsheets that live alongside the systems.

### Trace the flows

We follow selected key figures from the report back to the source system.

### Measure quality

We check completeness, timeliness and contradictions and make them visible with metrics.

### Design the target

We define leading systems, data flows and responsibilities and agree them with you.

### Two revenue figures for the same quarter

Sales and controlling report different revenue figures for the same quarter. Each number is correctly calculated in its own right, but they come from different systems with different cut-off dates. We trace both numbers back into the source systems, agree a binding definition with you and determine the leading system. From then on the monthly report shows one number, and the time spent on reconciliation is freed up.

- Three reports, three different numbers
- Before a migration or system replacement
- Before AI is meant to work on your data

Understand through Architect. In the BEIA, data is a layer of its own; in BISA 1, data flows, interfaces as well as cloud and SaaS are among the areas examined.

### Do I have to replace systems for this?

No. We connect the systems you already have. Only what is demonstrably redundant is switched off, and only after a period of parallel operation with reconciliations.

### What is data lineage?

The traceable path of a figure from the source system to the report. For audits, for example under BCBS 239 or DORA, it is a central piece of evidence.