Data Governance

“More and more organizations realize that data governance is a necessity; however, they lack experience in implementing enterprise wide governance programs with actual, tangible results.” –Gartner, 2020

Data is at the heart of a modern company's strategy.

Companies have now the opportunity to capture massive amounts of diverse data; with this comes also the responsibility of having a discipline to maximize the value of data.

A company needs Data Governance to manage the ever increasing volumes of data, to optimize its data processes, and to have an effective data accountability structure. All this will lead to increasing the quality of data, decreasing the risks associate with data, and transforming data into a corporate asset that is understood, trusted, and properly used in the decision-making processes.

Efficient use of Data to empower Business

Methodology

Our approach

Design // Implement // Govern

Our Data Governance Methodology consists of 3 phases: Design, Implement, and Govern.
When we developed it, we designed it to be flexible, practical, and measurable
– the three success criteria our clients are looking for.

We help you establish the data roles, processes, and tools that ensure:

  • Data is understood and trusted
  • Data has the level of quality required by your business processes
  • Data processes are compliant with internal policies and external regulations
1. Design

Foundation

Maturity Assessment // Data Strategy // Data Principles // Data Policies // Operating Model

As a first step, the Design phase is intended to lay foundation for Data Governance by:

  • Performing a Data Maturity Assessment
  • Designing the Data Governance Operating Model
  • Defining the Data Strategy, Data Principles, and Data Policies

Only with these, you will be able to have:

  • a common understanding of your current capabilities and opportunities,
  • an effective internal organizational model, with defined data accountability roles and responsibilities,
  • and a clear direction and vision on the desired state of data, completed with guiding principles and rules on what needs to be done to achieve a proper governance of data.
2. Implement

Data Governance Maturity Model (DGMM)

Data Domains // Critical Data Elements // Data Roles // Data Quality // Data Controls

In the Implementation phase, we incrementally and iteratively apply the DGMM methodology.

DGMM is objectively assessing the capability of our clients to define, manage, and use their data in accordance with the data strategy, data principles, and data policies previously defined.

Incrementally, because a practical approach dictates that at first the focus should be on the critical data for the prioritized data domains, and then, as we progress, increase the scope to gradually include all data domains.
Iteratively, because each time the scope is increased, the same standards have to be applied in order to achieve governance for the additional data domains in scope.

3. Govern

Continuous

Maintain // Monitor // Manage

The Governance phase is an ongoing phase and should be planned to last well beyond the initial implementation and to continue delivering for as long as you want to have data at the level of quality that your business processes require.

For this, we make sure that by reaching this phase you have all the capabilities and tools necessary to maintain data quality and data roles, to monitor data metrics, and to manage data controls.

Get a realistic assessment

Data Governance Maturity Check

Data Governance as a Program

Maturity Assessment

We perform an initial assessment of your current data maturity status by analyzing 3 key dimensions: People, Processes, and Technology. This results in a Maturity Report, completed with our recommendations in terms of scope and implementation roadmap.

Operating Model

Because people are at the center of Data Governance, we advise our clients on how to organize internally in order to establish and achieve the governance of data. This includes identifying the right persons for the specific data accountability roles and their responsibilities.

Iterative Approach

For the first iteration, the focus is on prioritizing the critical data. During the first iteration we also evaluate the use and fit of data lineage and data catalog tools.
The subsequent iterations are focused on increasing the data scope to gradually include all data domains.

Change Management

Throughout the implementation we advise on change plans and techniques to increase the adoption rate.
Training is an effective way to facilitate change and also provides a platform for interactions. Communication keeps all informed and involved.

Professional Services

Maturity assessment
Definition of scope and roadmap
Data governance implementation
Tools selection & configuration
Monitoring and reporting
Change management and training
Follow-up audit and long-term coaching

Iterative Approach

For the first iteration, the focus is on prioritizing the critical data. During the first iteration we also evaluate the use and fit of data lineage and data catalog tools.
The subsequent iterations are focused on increasing the data scope to gradually include all data domains.

Maturity Assessment

We perform an initial assessment of your current data maturity status by analyzing 3 key dimensions: People, Processes, and Technology. This results in a Maturity Report, completed with our recommendations in terms of scope and implementation roadmap.

Change Management

Throughout the implementation we advise on change plans and techniques to increase the adoption rate.
Training is an effective way to facilitate change and also provides a platform for interactions. Communication keeps all informed and involved.

Operating Model

Because people are at the center of Data Governance, we advise our clients on how to organize internally in order to establish and achieve the governance of data. This includes identifying the right persons for the specific data accountability roles and their responsibilities.

Professional Services

Maturity assessment
Definition of scope and roadmap
Data governance implementation
Tools selection & configuration
Monitoring and reporting
Change management and training
Follow-up audit and long-term coaching

Our Partner

Get in touch with our Data Governance experts