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Data Management & Governance

Data Management and Data Governance

“Data is a valuable asset”

We ensure that data becomes a strategic advantage. For our clients we implement robust governance frameworks and data management practices, protecting data integrity, ensuring compliance, and making sure that algorithms follow ethical standards.
Christian Verhagen
Christian Verhagen

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Maintain control over your data

Data management ensures that you maintain control over your data throughout its entire lifecycle. It guarantees data quality, ensures awareness of master data and metadata, and facilitates the sharing and utilization of data. Data governance, on the other hand, ensures active management of your data. It involves assigning ownership and overseeing data management. Together, these practices allow you to maintain control and translate data into valuable insights.

Non invasive data governance

Data governance involves assigning the right tasks and responsibilities at the appropriate levels, enabling the organization to effectively manage data. Questions arise about who is responsible for data policies, critical data assets, or data quality—for instance, roles like the Chief Data Officer (CDO) and Data Steward have gained prominence in recent years but are still relatively new. Moreover, their relationship with the existing organizational structure raises questions. Where does the CDO's responsibility begin and the CIO's end, or can they be integrated?

In most cases, the tasks are not entirely new. Organizations are already working with data, often with a designated contact for tasks such as ensuring data quality. Our approach focuses on making existing structures explicit and strengthening them so that data management occurs at all levels of the organization. We take a non-invasive approach, considering the organization and its employees. Additionally, our perspective extends beyond the organization itself to how data is shared, whether in chains or data ecosystems.
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The National Data Podcast

The podcast for data-driven organizations, with inspiring stories about data, algorithms and artificial intelligence (AI) in the public sector. In 20 minutes, you will be updated on the latest developments in data and hear how governments are using data and technology to address societal issues.

Standards and Data Quality

Data only becomes valuable when data quality is assured and meaning can be derived from it. Data management is responsible for this by structuring data, translating it into architecture, and assigning meaning to data through definitions, master data, and metadata. Our experts translate these aspects of data management into practical applications and establish the relationship with data governance. We align with standards and best practices, such as DAMA DMBoK, a globally recognized framework that provides guidance for data management. We translate this into practical solutions and help enhance the data maturity of the organization step by step. We do this with consideration for the organization and its employees.

Additionally, we offer training in the field of data management, including the Certified Data Management Professional (CDMP) program. This is done in collaboration with DAMA, with whom we have a partnership based on our shared ambition to improve the maturity level of data management.

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