Assess Data

Data Governance

The difference between your data having potential, and it being the most valuable asset your organization will ever possess.

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The root of every data ambition

When your users trust your data, they will use it more freely
and innovate more creatively – sparking a data-driven culture.

Data Quality

Data Security

Data Ownership

Compliance

Data Science

Accessibility

Consistency

Our heritage in data governance

For more than 10 years, we have put data governance in its various forms at the heart of a series of data services.

Organizations’ data privacy concerns and data residency needs drove the design of our public cloud platform, CloudCore – the first to offer data residency guarantees
Calligo launched the world’s first data privacy managed service, even before the arrival of GDPR.
For years, data governance, security and ‘privacy by design’ have sat at the heart of our data science services

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Our modern approach to
Data Governance Services

Our Data Governance consultants have unrivalled expertise in data management, compliance, security and data architecture, and will guide you through the overall strategy and detailed tactics of a data governance framework that will drive and protect your culture of data-driven innovation.

Data vision

What are your overall objectives and what do you need from your data to support them?

Data quality metrics

What does ‘good’ or ‘bad’ data mean to your organization? How does bad data affect your aspirations for data analytics or data science?

Data security

What processes and technology are required to continuously protect your data from external and internal threats?

Compliance standards

What national, international and industry-specific regulatory obligations do you need to ensure consistent adherence with?

Data management processes

Who owns the data and is responsible for its quality and accuracy? Who should have access to it and how is this controlled? And which data sources will serve as your single pillars of truth?

Business rules

How will your data management requirements be translated into processes for every user to understand and continuously follow?

Data architecture

Where will your data be best stored, in what formats and using what technologies?

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