Data Governance

We believe that the governance model should not be conceived in an isolated environment and then imposed as an external entity, as this could result in rejection by the organization. Instead, we recognize that every company, whether formally structured or not, already has an existing governance model—whether it is embryonic, partially outlined, or more developed. Importantly, people are already implementing this model, whether consciously or not.

The Path

We guide our clients through a journey designed to:

  • Value positive practices
  • Identify areas for improvement
  • Address obvious gaps
  • Suggest practical, cost-effective alternatives
  • Establish de facto roles within the organization
  • Our goal is to empower the entire organization by emphasizing the importance of consistently implementing the governance model, with an eye toward both immediate results and long-term sustainability.

Starting with the agreed formal structure, we then provide a customized Data Architecture Framework, one that is feasible and implementable within optimal timeframes. In collaboration with stakeholders, we select the most appropriate tools and methodologies for their specific context, ensuring alignment with the established practices.

Metadata Collection

Data Intelligence and Metadata Management tools are extensively employed to capture metadata from databases, data models, integration systems, and business intelligence tools. This allows for comprehensive, automated documentation of the data lifecycle, from source to data warehouse, reports, and analytical applications, outlining the transformation lineage.

The metadata collection process facilitates the publication of a Data Catalog, a key resource in tackling the challenges of data literacy and data democratization. The catalog functions as a “digital data library,” providing a comprehensive overview of available data resources, enabling users to easily locate relevant data and understand its usage.

Data Administration

The correct approach to data management lies at the intersection of formal rules and the operational needs of daily data management, ensuring that data remains accurate, accessible, and secure.

This operational focus is represented by Data Administration, which maintains and evolves the Data Architecture framework with detailed insights.

We assist clients in establishing a Data Administration Office if not already present, assigning it the central responsibility for the controlled evolution of the Enterprise Data Model, Data Dictionary, and associated glossary.

Tools

We support stakeholders in selecting, adopting, and evolving appropriate support tools, including enterprise data modeling cases. Together, we define the modeling rules and standards, ensuring control, efficiency, clarity, and consistency in the design of data models. We also conduct audits to verify their application.

Additionally, we provide Data Modeling expertise, where experienced professionals act as mentors to delivery teams, helping maintain and evolve the Enterprise Data Model through a controlled approach to promoting data structure changes.

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