Data Quality

Our vision

Why should we care about the quality of the data? Inaccurate or poor quality data considerably reduces the performance of a business, customer satisfaction, and employee job satisfaction, resulting in additional costs or a loss of income for an organization. Which solution should you put in place to obtain high-quality data?

By using Data Quality Management (DQM), which provides a set of tools and best practices that can be applied throughout the data lifecycle to ensure quality. Various factors can affect data quality, including the growing volume of data to be managed, the heterogeneity of sources, different application silos, lack of training, and more.

Your benefits

The benefits of a Data Quality Management approach vary according to the focuses identified based on the organization's needs. In general, the following topics are put forward:

Reduced operational costs
More effective marketing campaigns
Improved cross- and upselling
A better understanding of the customer
Improved regulatory and compliance efforts

Our Added Value

We are one of Belgium’s leading providers of DQM project consulting and implementation services.

With our proven methodology, with a strong focus on the collaboration between business and IT, we have been successfully delivering projects for various industries.

Why us?

Our teams, which comprise of both business experts and solutions experts, are highly qualified to respond to your specific issues and technical challenges. As such, we are able to deliver DQM projects end-to-end.

How we can help you

Our Data Quality Management approach is built around a sustainable process that includes measuring, correcting, and controlling data quality and establishing best practices for data governance.

Pragmatic examples:

Marketing: An incorrect customer address means a follow-up letter or customer solicitation that never arrives. Result: The sales and ROI associated with your campaign are reduced.
Invoicing: Invoices with incorrect information usually results in later payments, re-work and potentially cash-flow problems.
Purchasing: Incomplete or unconsolidated partner information may result in negotiations based on inaccuracies or lead to an agreement with an insolvent supplier.
Management control: Data that is not supplied under real purchasing or delivery process conditions can prevent management controls from detecting potential overcharges by suppliers.

Invest in your data quality through a structured Data Quality Management approach

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