What Is Data Governance?

In general, governance refers to the way the organization goes about ensuring that strategies are set, monitored, and achieved (Rau, 2004, p.35). Thus, governance implements a strategy by means of oversight and control mechanisms (Tiwana & Kim, 2015) and complements strategic as well as operational tasks: Strategy is doing the right things, operations are doing things right, and governance is ensuring that the right things are done right.  

In analogy, data governance links strategic data monetization initiatives with their daily execution to guarantee a return from data investments. 

Keyvisual-Data-Governance
The CC CDQ defines data governance as follows

Definition

Data governance defines roles and assigns responsibilities for decision areas to these roles. It establishes organization-wide guidelines and standards, and it assures compliance with corporate strategy and laws governing data. (Weber et al 2009) 

  1. Data Governance determines the activities that must be undertaken in order to manage data like a true asset 
  2. Governance defines who in the organization takes care of which data management activity 
  3. Solid data governance also determines the accountabilities, responsibilities and decision rights for the people who take care of data 
The benefits of an effective data governance framework are threefold: 

Why Do We Need Data Governance?

  1. Having clear responsibilities for data and data management speeds up the implementation of projects. Many projects depend on data, in particular the ones that push enterprise-wide business process integration, establish analytics, or address compliance requirements.
  2. Data governance is also the foundation for robust and sustainable data quality improvements. If it is not defined what good quality looks like (i.e. creating governance policies and guidelines) and ensured that these standards are adhered to, data quality is left to chance.
  3. Implementing effective data governance also contributes to increasing data’s value. If data is not used, it has no value. Data governance ensures that data issues are solved, and that data is "fit-for-purpose" for being used in business processes, for decision-making and in business models
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This CC CDQ research briefing explores data management challenges in large organizations and why traditional central governance models struggle with data at scale. It introduces a federated data governance model, emphasizing a hub-hub-spoke framework for balancing decentralization and coordination. It also highlights the essential role of the Chief Data Office (CDO) in guiding strategy, ensuring compliance, and promoting effective governance in distributed data environments.

CC CDQ Research Briefing - Federated-Data-Governance
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Reading

The CC CDQ Research Briefing emphasizes the growing importance of data governance and offers a comprehensive definition while elaborating on the dual responsibilities associated with data governance.

CC CDQ Research Briefing - Modern Data Governance
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Webinar

In this webinar, you will learn how to shift data governance from being a restrictive control function to an enabling one. Our speakers discuss the increasing scope of governance, the role of Data Offices, and the setup of federated governance. You will gain insights on how to guide their organizations towards a data-driven future.

Modern data governance webinar
Checklist

How to Develop a Data Governance Framework

Data leaders face several challenges when setting up data governance. One of them is that there are only a few guidelines on implementing data governance and that knowledge remains mostly tacit. Here is the good news: Defining a data governance framework isn’t rocket science. CC CDQ's reference model for data governance can help in developing and implementing a data governance framework. 

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Resources for you
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Ebooks, white papers, case studies, research articles, and templates: Here, you can find our data management publications at a glance.

Data Management Publications
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