Data Quality, the ally of Data business lines in data governance

Put Data Quality at the heart of your data assets.


Make the data-driven company a reality

Data Stewardship requires that you provide your teams with the means to enhance the value of the company’s data assets and, at the same time, strengthen its data culture.

Your prerequisite for this is to provide all employees with access to qualitative, usable and up-to-date data at all times. But having a data-driven company cannot be a reality when data is heterogeneous, obsolete or unstructured.

The data elements are then difficult, if not impossible, to use. To avoid this difficulty on the customer data front, DQE provides you with all the solutions you need to ensure Data Quality on incoming flows.

Use case

Accompany the data-driven transformation with Data Quality

Making the most of customer data starts with establishing and maintaining clean, up-to-date, standardized, centralized and merged data. This quality improvement and unification is done both in curative mode on the existing data and in preventive mode on the new data elements that arrive in the database.

DQE allows you to clean up existing databases by identifying any invalid contact information - email, mailing address, phone number. Its solution automatically corrects telephone numbers and mailing addresses that require it, and reports unusable email addresses. It also standardizes customer data to create the most complete and accurate parent record from all available information for each customer. Thanks to this quality improvement, you lay the foundation for the teams to make the most of customer data. It is also beneficial for the brand, especially in its relations with ISPs by reducing the rate of undeliverable emails.

DQE’s verification of customer data accuracy also applies on-the-fly to newly entered information, regardless of the point of contact. So, whether the information is entered directly by the customer in their digital journey, or by your company’s teams, the data entry assistance tools help to correct any error in the data. The quality and reliability of the customer data assets are thus maintained and intact.

In addition to the verified quality of the basic data, DQE allows you to unify customer data according to the merger criteria defined by your company. This fine-tuning and adaptability ensures that the best business line rules are applied to identify duplicates. In addition, the control of duplication thresholds prevents the creation of false duplicates with the risk of merging two distinct records mistakenly identified as the same customer and losing customer data. In terms of governance, you are guaranteed to make a consistent, exhaustive, and readable database available to all users.

With an optimal Golden Record, employees can work with confidence with the company’s customer data and are encouraged to launch new data-driven initiatives. This makes it easier to develop a data culture within the company, as well as innovations in customer data. Thus, DQE’s solutions provide data departments with a major contribution to creating a data-driven company.

Thanks to the DQE solution,25,000 email addresses invalidated in the past by ISP servers that were no longer responding could be requalified as existing and reachable. Bip&Go was able to to re-establish contact with these customers, propose new offers and generate additional revenue.

Michael Bouyer Data Protection Project Manager - Bip&Go

Thanks to the DQE technology, we have access to a very interesting quality of results. This performance allows us to correctly measure data quality within the BPCE group and all its banking establishments.

Antoine Mantelier Head of Group Data Management - BPCE

Within a few months of the deployment of the DQE entry assistance, our vendors have entered into the database complete and verified data of 20% more additional customers, meeting our recruitment objectives.

Ludivine Jallet CIO - Pacific Pêche

DQE allows us to know the real proportion of duplicates in our database, to deduplicate them and to find the exact number of customers present in the database - fundamental information for the Hess Automobile e-commerce project.

Simon Amaniera Group Chief Digital Officer, Hess Automobile

We were looking for a Data Quality Client solution that exactly met the expected functionalities (cleansing and merging), that was technically robust and that I could master - that's exactly what I found with DQE One!

Joris Dulac CRM Manager -