Data Governance

Define processes, roles and responsibilities for reliable and transparent data management across the entire organization

The road to effective data governance

Data governance framework

Top-down approach

What is data governance?

The understanding that high data quality is an elementary prerequisite for business success has now become established in almost all companies. Nevertheless, many companies fail in practice to maintain the quality of their data at a high level over the long term. In search of the causes, it turns out that a suitable organizational framework with processes, roles and responsibilities for transparent and reliable data management is often lacking − a framework that data governance can provide.

Data governance ensures that data is managed and maintained in a uniform and disciplined manner. It defines clear responsibilities, establishes data ownerships, ensures a stringent security concept, and designates clear roles that are responsible, for example, for compliance with data quality and implement the strategic requirements from a functional perspective.


  • Defined responsibilities

  • Clearly divided data ownerships

  • Neatly defined and documented processes

  • Improved security

  • Fulfillment of compliance guidelines and legal requirements

  • Established data stewards

Free white paper on data governance

Data governance provides the organizational framework for consistent, disciplined data maintenance and high data quality. The white paper “Data Governance – How to create the basis for permanently high data quality in your company” describes why clear responsibilities and unambiguous roles are decisive prerequisites for ensuring high-quality data. Using concrete practical examples, it becomes clear how data governance promotes corporate success.

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Objectives of data governance:

  • Create transparency and trust in data

  • Ensure reliability of data

  • Ensure data security and privacy

  • Ensure data availability and accessibility

  • Optimize data management

Challenges of data governance:

  • Lack of management commitment

  • Unclear responsibilities and accountabilities

  • High complexity of the data landscape

  • Unclear scope

  • Accompanying change management and acceptance

Why data governance is indispensable for medium-sized companies

Data is increasingly becoming a decisive competitive factor. Mid-sized companies that manage and use their data effectively are able to make informed decisions and operate more successfully in the business world than their competitors. With a functioning data governance, they ensure that they access high-quality data and improve their decision-making.

Clear roles and responsibilities for data maintenance, access, and quality help mid-sized companies make their processes more efficient. In addition, data governance ensures that applicable compliance requirements are implemented and legal requirements regarding data protection are met.

Data governance is particularly important for mid-sized companies in order to ensure the security, quality and effectiveness of their data, to meet compliance requirements and to strengthen their competitiveness.

Data governance describes a holistic system that determines, among other things, who in an organization has access and authorizations with regard to corporate data. It covers people, processes, and the tools and mechanisms used for this purpose.


The road to effective data governance

In order for companies to make their data a long-term success factor, they must maintain their data quality at a permanently high level or increase it continuously. An effective data governance plays a decisive role in achieving this goal.

The establishment of governance processes ensures consistently high data quality. Data governance creates stable strategic conditions for effective data management.

We address all relevant topics related to data governance in a pragmatic top-down approach (see below):

  • Based on the strategies, challenges and goals of the company, we analyze the existing processes and define an organizational model with corresponding roles.

  • Based on this, we define the responsibilities in a RACI matrix (RACI = Responsible, Accountable, Consulted, Informed) and assign detailed field responsibilities for all relevant data objects.

  • In a final step, we take care of the handover for implementation, plan the governance roll-out and install the new organization.

Your contact person


Michael Müller
+49 7131 2711-3000

The development of a data governance strategy is the foundation for the sustainable increase of data quality in the company.


Best Practice: The IBsolution Data Governance Framework

Data Governance Framework englischBased on our many years of experience in data management, we have developed a data governance framework with six pillars that creates the strategic framework for successfully managing data and permanently ensuring high data quality. This includes setting up a data governance organization and integrating it within the corporate structure. The definition of roles serves to clarify responsibilities and to create a sustainable role concept for the organisation. The tasks and activities that have to be performed within the framework of data governance are determined in the definition of tasks. This not only determines what needs to be done, but also which departments of the company perform the tasks.

The definition of processes aims to describe, document and optimize the existing data processes. Assigning responsibilities creates a clear allocation of the role concept on the one hand to the tasks and processes on the other hand. The responsibilities are detailed with the help of a RACI matrix. In this context, the definition of ownership for the various data objects is also part of the process. Data maintenance defines how the theoretical descriptions are to be transferred to operational data management. The aim is not only to define the data maintenance processes from a functional point of view, but also to clarify the technical implementation and describe the change management.

How we proceed within the context of the data governance framework

Vorgehen im Data Governance Framework englisch neuAlthough a standardized approach to data governance has proven itself, the individual characteristics of each company must be taken into account in every project. Data governance only has a chance of success if it is in line with the corporate strategy and supports it in the best possible way.

An analysis of existing processes provides information about how data management is currently organized in the company. Based on existing processes, an optimized set of processes is developed in line with industry standards and best practices. In parallel, the data governance organization within the corporate structure must be defined. Among other things, this involves the question of whether activities should be mapped centrally or organized in local units.

The next step is to derive tasks from the target processes and a role concept from the data governance organization. A RACI matrix links tasks and roles. In addition, the field ownerships are defined: Who has tactical responsibility for the fields? Who is responsible for operational data maintenance?

Once this theoretical framework is established, the roll-out into the organization takes place.


Our top-down project approach


Strategy for data management

  • Support in deriving the data strategy from the corporate strategy

  • Support in the definition of measurable goals and the creation of a data roadmap

  • Joint development of a communication and change management strategy

Data organization

  • Definition of an organizational concept
  • Establishment of an operating model (coordination and methods)
  • Support in setting up the organization and roles (nominations, definition)
  • Support during the transition and roll-out of the operating model

Process framework

  • Review and, if necessary, documentation of existing processes in the data environment

  • Support in the development of optimized target processes and tasks

  • Definition of the tasks in RACI

  • Documentation of the final framework, based on customer standards

Ownership mapping

  • Preparation of ownership templates and task definition

  • Coordination and moderation during the development of the ownership mapping

  • Support for the introduction of a data dictionary

Data maintenance processes and data quality

  • Visualization of data maintenance processes (creation, modification, enhancement, blocking, deletion, ...)

  • Definition of the working model for process governance

  • Process documentation and training of process participants

  • Support in setting up data quality KPIs and a monitoring system

Data management organization

  • Setting up the data management organization

  • Supporting the coordinated roll-out with the SAP S/4HANA migration

Further information and offerings related to data governance

Data governance in finance transformation | IBsolution

Data governance: The key to successful finance transformation

Data governance plays a key role in finance transformation by determining who the proper people and roles are to handle financial data, approve changes, and ensure its quality.
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Data governance as a strategic success factor | IBsolution

Why data governance is a strategic success factor

The realization that high data quality is an elementary prerequisite for business success has meanwhile become established in almost all companies. Data governance makes an important contribution to high-quality data. Nevertheless, only 5% of companies have fully established data governance.
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Best practice examples for data governance | IBsolution

Best practice examples of the benefits of data governance

Data governance provides the structural foundation on which effective and successful data management can be built in a company. In day-to-day business, there are always situations in which data governance helps to solve problems, overcome challenges and achieve competitive advantages.
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Data Governance | IBsolution

Data governance: basic framework for data management

A stable strategic foundation can provide the best possible support for the challenge of operational data management and maintenance. This foundation for data management in the company is called data governance.

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Implementation of data governance | IBsolution

Strategic implementation of data governance within a company

Data governance encompasses people, processes, and technologies required to manage and protect data assets. In this webinar, we will show you how to set up data governance in your company.

Watch now

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