Reference data sources

Benefit from integrated data sources to improve master data quality

Validate, curate and enrich your business partner master data by using external data sources. The CDQ Cloud Platform provides access to 70+ trustworthy open and premium data sources and offers easy data mapping and system integration.
Simplify data entity relationships

Build your single source of truth with external data sources

Integration of external data sources for data enrichment or validating business partner and address data is a prerequisite to boost business data process and your overall data quality. And it doesn’t have to be challenging. CDQ Cloud Platform is your external data connector to a wide selection of open and commercial data sources covering over 300 countries worldwide and almost 1000 legal forms. Activate your preferred business partner data sources out of the 60 active suppliers for leaner master data management. Additionally, our Data Sharing Pool has over 2 million business partner records available for Data Sharing Community members.

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Webinar

Unlock your business potential through external data

In our free webinar on demand Dr. Tobias Pentek and Dr. Markus Eurich show you how to gain competitive edge with reliable external data and innovate your business.

CDQ Webinar – Leverage External Data For Business Success
CDQ Data Sharing Pool

Clean data you can trust

Business partner information from open and commercial data sources and our Data Sharing Community is normalized, merged into a complete dataset, and checked against our 2,500+ well-developed data quality rules. With CDQ Cloud Platform, you can select your preferred reference data sources through a single interface, create augmented record out of it and flawlessly import a clean record into your system.

Some of our 70+ integrated data sources

ABR logo
Companies hHouse logo
data.gouv.fr logo
Dun & Bradstreet logo
economie logo
GLEIF logo
Google logo
HERE logo
KBO logo
United States Securities and Exchange Commission logo
Zefix logo
At a glance

Easy integration of reference data with CDQ Cloud Platform

Data mapping

Each data field you want to use must have a defined corresponding counterpart in your database. For example, UK Companies House provides address information in the semantically ambiguous data fields such as “AddressLine1” which require mapping and transformation into your data model.

What is the CDQ Cloud Platform?

Data curation

After mapping your data, you need to curate it. For example, if you look at the information from Zefix, you can see that the “address” field contains a mix of information (street name and house number). Our software developers found a solution for these types of discrepancies and wrote the appropriate code so that the required information is provided in a semantically unambiguous and structured representation.

Integration

To give you an easy technical solution for how to integrate this data, we have programmed bots that monitor updated dump files (usually provided in various formats such as CSV, JSON, or Excel). Our expert team programs the bots to ensure that new data is available for our Data Quality as a Service users.

Maintenance

Using open reference data sources is beneficial. However, making this data usable requires a lot of effort. Additionally, these integrations involve continuous maintenance. We monitor changes to the data as well as the data models and implement these changes accordingly.

Reduce your data maintenance costs by 40% with CDQ Zero Maintenance solution

 

More useful insights for you

CC CDQ resources
Explore

In our Wiki, CC CDQ members can find the collective knowledge of the community: publications, work reports, co-innovation researches, and much more know-how on data management.

CC CDQ Wiki
Data management framework
Learn more

The Data Excellence Model offers support and guidance for practitioners in the implementation of data management by defining major design areas, while at the same time supporting the transformation into a digital and data-driven company.

CDQ Data Excellence Model

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