Data processes / 13
Clarify product data once. Distribute it selectively.
The ERP supplies master data, the PIM supplies text and a supplier provides technical attributes. Manual lists connect this information only temporarily. We create a defined data flow from each authoritative field to a validated channel export.
The starting point
A valid product is not automatically ready for every channel.
A product may be complete for an internal portal but still need an image, unit or translated text for the webshop. Variants have different required attributes from their parent products. Pricing and master data also change at different frequencies.
We separate product identity, enrichment and publication. Channel rules are maintained as verifiable requirements rather than hiding missing content behind generic defaults.
What DataSource delivers
Connect sources. Validate quality. Distribute.
Connect sources
Define field ownership between ERP, PIM and suppliers. Distinguish product numbers, variant IDs and supplier references explicitly.
Validate quality
Normalize units, attributes, variant relationships and media references. Validate required fields and permitted values for each target channel.
Distribute
Export approved data states only. Transfer changes selectively and report rejected products with understandable error context.
Technical scenario / Illustrative example
Three sources, one approved product model.
Illustrative field mapping for a product. Channel validation determines publication. A missing image can prevent shop approval, for example, without deleting the ERP product.
Example data and proposed rules. The actual interfaces and business rules are assessed for your project.
ERP → sku, unit, taxClass
PIM → title, description, imageRefs
Lieferant → technicalAttributes
shopReady =
eindeutige SKU
+ Pflichtattribute vollständig
+ Medien freigegeben
+ Varianten gültigError handling, security and operations
Variants: validate and operate.
Variants
Validate parent-child relationships and attribute combinations before export. Do not silently publish duplicate combinations or variants with missing parent products.
Media
Account for permitted sources, usage rights, file sizes and availability. External references do not guarantee that images remain available.
Channels
Use marketplace or shop access only through supported, authorized interfaces. Assess vendor, edition and channel constraints before the project starts.
Technical questions
Details that matter before implementation.
ERP · PIM · Variants · Attributes · Channels · Data quality
Is this the same as a WooCommerce integration?
The product data architecture spans channels. A WooCommerce integration implements that model for the specific shop API and its products and variants.
Can supplier data be imported automatically?
Yes, when access, usage rights and the data contract are clear. Field priorities prevent supplier text from overwriting your approved content.
What happens to discontinued products?
Discontinuation, blocking, archival and deletion are handled separately. A channel may have different requirements from the authoritative master data system.
For technical clarification
Start with your actual workflow.
Prepare sources, field ownership, target channels and two typical products including variants. Identify known required fields, media rules and approval issues.
In our initial discussion, we clarify available access, data ownership and a narrowly scoped first data flow. We then agree on scope, responsibilities and commercial terms.
Anonymized examples are enough to get started. Please do not send passwords, tokens or personal data from production systems in your initial inquiry.
Related challenges
Your next connection in context.
Connect WooCommerce to your ERP
Products are maintained in the ERP, edited again in the shop and updated through files. We connect the data models and clarify which information is owned by the ERP and which remains in the shop.
Automate CSV imports
The file arrives every day. Someone corrects columns, uploads it and then checks error messages. DataSource turns this recurring task into a documented import with clear rules for incomplete and invalid data.
JSON / XML data transformation
The data is technically readable but still rejected. Field names, types or structures do not match the target application. We develop traceable mappings that also handle empty values, edge cases and changes to the source format.