Data Sharing Community

Welcome to the Portal of the CDQ Data Sharing Community

Summary

We are excited to announce the integration of the California Business Register into CDQ's Business Partner Lookup service. This new data source enhances our coverage of businesses registered in California, providing valuable insights to support compliance, data enrichment, and risk management efforts.

Details

The California Business Register data is sourced from the California Secretary of State's BizFile Online database and the publicly available business entity dataset. It contains over 8 million records and is updated weekly to ensure the most current information is available.

Each record may include the following details:

Entity name
Entity number
Business partner status
Address information, including:
- Principal address
- Mailing address
- Principal address in California (if applicable)

Augmentation Configuration Support in Generate Golden Record Endpoint (11 March 2025)

Overview

We have enhanced the Generate Golden Record endpoint by introducing support for Augmentation Configuration. This improvement offers greater flexibility and control over the Golden Record generation process by allowing users to specify a configuration that defines how data should be enriched and prioritized

New functionality

The Generate Golden Record endpoint now accepts an optional parameter called configurationId in the request payload.

If a valid configurationId is provided: The specified augmentation configuration will be applied during the Golden Record generation process.
If no configurationId is provided: The system will automatically apply the default augmentation settings or the one assigned to the API key used in the request

Payload example:

{ "cdqId": "DE.RC:B8537_HRB739690", "configurationId": "67cac20c5ffe2e2117ff2ca3" }

Benefits

Improved control over data enrichment by specifying desired augmentation rules.
Ensures consistency in data output by leveraging predefined configurations.

This enhancement is now available for use in the API. For additional details or support, please refer to the API documentation.

Seed Updates for Customer-Modified Business Partners (7 March 2025)

We are introducing a new feature that automatically generates a seed update whenever a business partner (BP) is modified within the customer mirror. This update allows you to quickly compare the latest BP details against those in the reference data source.

Updates are generated only if customer changes impact the CDQ data model (a change of just a record has no influence). Updates created by this trigger receive a special tag: CUSTOMER_UPDATE_TRIGGER, which makes them easy to identify and track.

These enhancements provide greater visibility and control over business partner data, ensuring that any changes in the customer mirror are promptly reconciled with data from reference sources. For more information or assistance, please contact our support team.

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Data model

An important prerequisite for collaborative data management is a common understanding of the shared data. For the CDQ Data Sharing Community, this common understanding is specified by the CDQ Data Model. The concepts of this model are defined and documented in this wiki which can be used as a business vocabulary. Moreover, the wiki provides a machine-readable interface to reuse this metadata by using semantic annotations.

This is a graph with borders and nodes that may contain hyperlinks.

Data maintenance procedures

A procedure is a common standard or "how-to" for a specific data management task. Within the CDQ Data Sharing Community, companies agree on such procedures to ensure similar rules and guidelines for similar tasks. For several countries, the CDQ Wiki provides such information, e.g. data quality rules, trusted information sources, legal forms, or tax numbers. Try

or select another country from the list.

Data sources

Active data sources	Records
Data source BR.RF	64,547,681
Data source CDQ.INTEL	50,448,418
Data source VIES	50,000,000
Data source FR.RC	40,280,202
Data source US-CA.BER	8,704,706
Data source GB-EAW.CR	8,575,386
Data source US-FL.BER	6,112,782
Data source JP.CR	5,589,016
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The CDQ Data Sharing Community uses a collaboratively managed reference data repository. This incorporates the integration of external data sources for enriching or validating business partner and address data. Examples of available data sources are 316 countries (e.g. WORLD (World), AT (Österreich, Austria, Autriche, 奥地利), BE (Belgien, Belgium, Belgique, België, 比利时)), 993 legal forms (e.g. ), and 72 active business partner data sources (e.g. Data source CDQ.POOL, Data source VIES, Data source CH.UIDR).

Metadata and Standards: Metadata-driven Data Quality

Data quality plays a pivotal role in ensuring compliance with legal, regulatory, and industry standards. One of the core challenges in achieving high data quality is adhering to dynamic data requirements that evolve due to changes in national regulations. These requirements vary by country, making it essential for businesses to track and update compliance criteria continuously.

In many countries, official company information is available as Open Data, but the lack of a standardized data model or provision method complicates the process of integrating this data. The Data Sharing Community actively collaborates to identify global data requirements and reference data sources, whether Open Data or commercial.

Metadata	Short description
Administrative area metadata	Managed reference data for administrative areas with language-specific terms and short names according to ISO 3166-2.
Bank account metadata	Managed reference data for bank accounts worldwide.
Business identifier metadata	Managed reference data for types of identifiers per country.
CDQ Data Model	Basic data concepts of CDQ Cloud Services.
Compliance lists metadata	Managed reference data about compliance lists considered in the sanction and watchlist screening services
Country metadata	Managed reference data for countries with language-specific names and short names according to ISO 3166-2.
Data Quality Rules	Documentation of data quality rules with explanation and technical constraints to validate business partner data records.
Data quality rules function library	Data quality rule functions are methods implemented in a programming language for being used in data quality rule implementations. They can be e.g. used in custom data quality rules similar to functions employed by business users in popular spreadsheet applications such as Microsoft Excel.
Legal form metadata	Managed reference data for legal forms with official and commonly used abbreviations and corresponding country.
Locality metadata	Managed reference data for localities, such as exonyms.
Post code metadata	Managed reference data for post codes
Postal delivery point metadata	Managed reference data for postal delivery points, such as Post Office Boxes used for identification, extraction, harmonization and standardization.
Registration authority metadata	Managed reference data for issuing bodies of identifiers
Street metadata	Managed reference data for thoroughfares of type Street (CDQ.POOL) used for harmonization and standardization.

Data Quality Rules

Transformation of human-documented data requirements into executable data quality rules is mostly a manual IT effort. Changing requirements cause IT efforts again and again. Some checks, e.g. tax number validity (not just format!), require external services. Other checks, e.g. validity of legal forms, require managed reference data (e.g. legal forms by country, plus abbreviations). Continuous data quality assurance (i.e. batch analyses) and real-time checks in workflows often use different rule sets.

Data requirements and related reference data are collected and updated collaboratively by the Data Sharing Community. Data quality rules are derived from these requirements automatically. All data quality rules are executed behind 1 interface, in real-time. Batch jobs and single-record checks use the same rule set and can be integrated by APIs.

For proving that a data quality rule is content-wise correct we maintain supporting document(s) per data quality rule which share the rule's source. This could be:

a public authority source
any other trustful webpage
a data standard of a specific community member

We manage the URL (if any), a screenshot of the relevant parts (if any) and the source's name (e.g. Community member data standard, European Commission, National ....) See Identifier format invalid (SIREN (France)) as an exemplary rule that was specified and implemented based on information provided by the OECD.