Manufacturing

Governed, traceable data for every plant.

One platform for catalog, glossary, lineage and data products. Tell us what is on your desk and we will show you the part that matters.

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What is on your desk this quarter?

What the program needs

A map before you move anything

Moving from SAP ECC to S/4HANA, or the warehouse to Snowflake, Databricks or Fabric, starts with knowing what depends on what.

What breaks today

Unknown downstream plant reports
Unused tables migrated anyway
Lineage lost in the move

With Dawiso

Catalog and lineage across SAP HANA, SAP BW and cloud platforms in one graph
Impact analysis through lineage before you cut over

250,000+ objects in 250+ Snowflake databases at Stora Enso

In production at European manufacturers and logistics operators

How it works

From the ERP table to the plant report, in one place.

Metadata scan · 4 sources

SAP HANA · ERPscanned
SQL Server · production datascanned
Power BI · plant KPI reportsscanning
Snowflake · plant martqueued

Tables, columns, reports and SQL are picked up automatically, with no manual cataloging.

Lineage · OEE by plant report

erp.production_orders
dwh.machine_events
plant_mart.oee_daily
OEE by plant

SELECT plant_id,
  availability * performance * quality
  AS oee
FROM dwh.machine_events ...

Column-level lineage parsed from your own SQL.

Regulation coverage

What each standard asks for, and how you show it.

Regulation	What it asks	Your evidence in Dawiso
GDPR	Know where employee, customer and supplier data lives	Personal data classified in the catalog and followed through lineage
EU AI Act	Documented data and controls for AI in quality and maintenance	Owners, definitions and lineage for the data that feeds each model
IATF 16949	Traceability and documented data processes in automotive quality	Column-level lineage from source to report, named owners per asset
ISO 9001	Documented processes and controlled changes	Change history and approval workflows, one glossary for quality terms

Customer story

One catalog for a global materials company.

Two Stora Enso workers in safety gear walking through a paper mill hall

Stora Enso · renewable materials

How Stora Enso cataloged its data from Snowflake to Power BI

Metadata harvested from 6 types of source systems through 50+ active ingestion pipelines, one business dictionary, and a data community that writes its own content.

8,700+: Power BI reports
1,000+: business terms
500+: users creating content

“A good solution does not stop with the software but includes people too. The Dawiso team has been and remains on hand, assisting with the adoption of the data catalog solution and with improving our data governance maturity.”
Stora Enso

Read the Stora Enso story

78 daysfrom the start of implementation to a fully operational solution

39,000+objects documented across 9 thematic spaces

Go-live

Fully operational in weeks, 78 days at P3 Parks.

Phase 1Connect and scanScanners read the ERP database, the warehouse and BI.
Phase 2Lineage and glossaryColumn-level lineage from your SQL, plant KPIs defined.
Phase 3Owners and workflowsStewards assigned, approvals on, audit trail recording.
Phase 4First traced KPI reportOne plant report traced end to end.

Questions manufacturers ask us

Does Dawiso integrate with ERP and production systems?

Dawiso connects to 40+ data sources including SAP S/4HANA, Snowflake, Databricks, Power BI, Oracle, SQL Server, Tableau, and dbt. For production and planning systems with no native connector, our REST API and MCP server enable custom integrations. See the full connector list on our Connectors page.

How long does implementation take for a manufacturing company?

Most manufacturing customers go live with a working catalog in weeks, depending on the number of data sources. P3 Logistic Parks went from zero to a comprehensive data governance platform in 78 days. Automated metadata scanning eliminates most manual work, and the SQL Parser generates lineage from existing code without custom development.

Can Dawiso handle multi-plant, multi-country deployments?

Yes. Dawiso is deployed at enterprise manufacturers with operations across multiple countries and hundreds of users. The platform supports multilingual interfaces, role-based access control per plant or domain, and scales to hundreds of thousands of scanned objects without performance degradation.

How does Dawiso support IATF 16949 and ISO 9001 compliance?

Dawiso maintains a complete audit trail of all changes to data assets - who changed what and when. Approval workflows enforce governance processes before changes take effect. Data lineage documents the traceability chain from source to report. These records are available on demand for quality audits and certification reviews.

Can Dawiso govern AI models used in manufacturing?

Yes. Dawiso catalogs AI and ML models alongside data assets - documenting model inputs, outputs, versions, training data, and owners. This supports EU AI Act compliance for high-risk AI systems used in quality control, predictive maintenance, and demand forecasting. Model governance in Dawiso works through the same catalog and lineage framework as your data assets.

What deployment options are available?

Dawiso is available as SaaS, on-premise, and hybrid with full feature parity. Manufacturers with data sovereignty requirements or air-gapped environments run Dawiso fully on-premise. Enterprise authentication via Azure AD, LDAP, and SAML is fully supported.

How is Dawiso priced?

Dawiso is priced per user, not per data source or scanned object. You can roll out governance to every team in your organization without per-connector or per-asset fees. See our pricing page or book a demo for a quote tailored to your organization size.

Bring one plant KPI report. We will trace it with you.

A 30-minute session with our manufacturing team, built around your report, your stack and your plants.