Data Sharing Community

Welcome to the Portal of the CDQ Data Sharing Community The CDQ Data Sharing Community is a trusted network of user companies to manage business partner data collaboratively.   CDQ data model       Support Metadata and Standards · Data Quality Rules · Data Sources  · Procedures

What's new? (RSS) Simplified Data Transformation After Mapping Changes (8 July 2025) You no longer need to use the API to transform data when there's a change in assigned mapping. Now, you can perform data transformation directly in the APPs interface. To apply transformations: Navigate to Data Mirror Management. Select your data source. Click on Start Transformation. Choose the country scope (optional). If no country is selected, the system will transform data for all BPs in the mirror where the mapping change is relevant. This update streamlines your workflow and reduces dependency on API calls. Monitor Status for Business Partners (27 June 2025) We’re excited to introduce a new Status feature in the Monitors module of the Data Clinic app. This enhancement provides visibility into the current state of Business Partners (BPs) within Augmentation and Data Quality Profiling monitors, helping users make informed decisions when downloading or reviewing BP data. Key Benefits: Avoid consuming incomplete data by easily identifying BPs that are mid-reprocessing. Monitor BP readiness and take action only when data is up to date. Streamline workflows by accessing real-time status data directly in the UI or via API. Status Overview: Each BP in a monitor is now assigned one of four statuses: Ready – The BP has up-to-date results and is ready for download. In Progress – The BP is currently undergoing processing or reprocessing. Retry – The BP requires processing has failed and needs to be reprocessed. Blocked – The BP cannot be processed due to an issue that needs to be resolved. Where to See It: Configuration Page: Get an overview of how many BPs are in each status category across your monitor. Data Review (Single Mode): Check the individual status of a selected BP during manual review. API Access: Status information is also available programmatically via our API responses. This feature aims to improve data accuracy, transparency, and efficiency when working with monitored BPs. Augmented Business Partner Report & Legal Entity Report v3 (26 June 2025) We’re excited to announce two enhancements to our reporting suite: the Augmented Business Partner Report and an updated Legal Entity Report. Augmented Business Partner Report This new report delivers the full results of augmentation monitoring for your business partners. You’ll see every proposed value alongside its original “before” data, plus all Update Assessment details—action taken (added, modified, deleted), classification, data provenance, similarity scores, and modification timestamp. Just like the existing Update Report, you can filter by summary classification and creation date to zero in on exactly what matters. Legal Entity Report (v3) The revamped Legal Entity Report leverages our latest curation logic to surface official register data—legal status, VAT registration, and any local attributes—alongside the same augmentation monitoring insights (action, classification, provenance, scores, and modification date). Both the new and legacy versions remain available, giving you flexibility to evaluate the improvements and switch over at your own pace. ... further results 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. 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 CH (Schweiz, Switzerland, Suisse, Svizzera, Svizra, 瑞士), DE (Deutschland, Germany, Allemagne, 德国), PL (Polen, Poland, Pologne, Polska, 波兰), US (Vereinigte Staaten, United States of America, États-Unis d'Amérique, 美国), or select another country from the list.

Data sources Active data sources Records Data source BR.RF 66,349,272 Data source CDQ.INTEL 53,424,836 Data source VIES 50,000,000 Data source FR.RC 41,793,664 Data source GB-EAW.CR 8,868,373 Data source US-CA.BER 8,842,285 Data source US-FL.BER 6,350,007 Data source JP.CR 5,646,543 ... further results 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.