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Master Data Matching#

Master Data Matching is a core part of the extraction workflow in DocuWare IDP. It helps you connect and validate extracted document data with your trusted master data, so workflows can identify the right entity and trigger the right actions automatically.

diagram For dedicated onboarding also use the Tour on the Master Data Matching page and the guide linked there. That is the recommended starting point for setup and guided onboarding.

mdm page

What Master Data Matching does#

Master data is the trusted ground-truth data from your internal systems.

When extracted values are compared with master data, the system can detect matches or differences. Based on the result, matching actions can be applied, for example:

  • replacing an extracted value with master data
  • adding a note to a field
  • clearing a field
  • flagging a field
  • marking a document as verified

Master Data Matching is part of the extraction process. The matching results are included in the extraction results and matching actions (notes and replacements) are documented in the field notes.

How it works#

  1. Connect a master data source

step 1 2. Map extracted fields to the matching master data fields

step 2 3. Create rulesets to define when a match is fulfilled

step 3 4. Define actions for match and no-match cases

step 4 5. Test the workflow and adjust the rules if needed

step 5

Master Data Source Connection#

You can upload and maintain your master data via the Master Data page. We support CSV files in all common separators and encodings.

In addition, starting with DocuWare version 7.14, it is also possible to import Select Lists as a master data source. To do this, the DocuWare user must have the “Manage IDP” right.

During the setup, you need to enter your DocuWare Cloud URL. You will then be prompted with a pop-up window to authenticate. Once the authentication is completed, you will see an overview of the available Select Lists in the platform.

These lists are imported as a one-time import and are not kept in sync automatically.

We are currently working on synchronous data synchronization as well as additional data source connectors.

add source

Rulesets and logic#

Once your master data source and mappings are in place, you can create rulesets. Rulesets define the logic that decides whether a record is considered a match.

You can create individual rules or rule groups, and combine them with:

  • AND: all rules must be fulfilled
  • OR: only one rule or group must be fulfilled

Each ruleset can trigger actions in two cases:

  • On Match: what happens when the rule is fulfilled
  • No Match: what happens when the rule is not fulfilled

Common actions include replacing extracted values with master data or verifying the document.

ruleset

Enrichment with custom fields#

Master Data Matching can also be used to enrich data that is not present on the document itself. This is useful for downstream processes, for example when you need internal IDs for issuers, creditors or business transactions.

You can also use enriched fields across multiple rulesets. For example, one ruleset can identify a vendor and write the vendor ID into a custom field and a later ruleset can use that field in its logic.

A common setup is to create a calculated string field, use a constant formula and leave the value empty. This keeps the field empty during extraction so it can be populated by Master Data Matching.

enrichment

Technical Limits#

Please keep the following limits in mind:

  • Master Data upload limit per tenant: 100 MB
  • Matching performance limits: up to 200,000 records per table and 15,000 rows per table
  • Ruleset nesting: limited to a normal use-case level and does not affect correct usage of rulesets

Import behavior#

At the moment, Master Data imports are one-time imports only. There is no continuous synchronization yet. To update master data, delete the old entries and import a new table.

Use Case Example#

If an invoice contains a vendor name like M. Mustermann GmbH, Master Data Matching can compare it with your master data and identify the correct vendor entry, such as Max Mustermann GmbH. If other fields like address or VAT number also match, the workflow can automatically replace or verify the extracted values.

use case