Building a Data Governance Framework

If you read our previous blog posts you probably noticed a certain trend. The gist is: we believe most organizations have more than enough data at their disposal and their aim is always to realise the full potential of this data. This is of course the sensible thing to do: data that is used well can help boost a company’s ability to compete on the market and increase its productivity. However this opportunity comes with certain risks. In the past few years the demand for proof of compliance to confidentiality guidelines as well as security and integrity of information has been risen by external forces.


The demand for compliance with regulatory, ethical and legal requirements concerning (sensitive) data is steadily growing. Data Governance Frameworks can create guidelines and rules that allow organizations to make informed decisions on how to manage data and realize its true value. As a side-effect a framework also helps to minimize complexity and costs and manage risks.



Oftentimes the question is what to do with with data used and created by humans as well as technology. Data governance provides the guidelines on the questions how to collect, manage and archive data that are needed. Ideally companies should develop a framework that includes everything from people and processes involved in the handling of data to tools and technologies needed to manage it.

Why do companies need a Data Governance Framework?

While it might have been the case in the past the assumption, that data is only used by the departments or teams that gathered it, is no longer realistic. In-house information is becoming a valued asset across the entire organization. It is no longer property of a single department. Therefore data and resulting information needs to be structured in way that is understandable to anyone–not only the distinct group of people that originally gathered the data.


Also the appropriate access rights have to be granted. Generally speaking the more people have access to the data within the company, the more the company needs to make sure everyone complies with the corresponding rules and policies. As mentioned before: ideally there should be a whole governance system that sets rules for every type of activity. It needs to answer ownership questions, address inconsistencies in the data across departments and provide solutions to the growing need of well structured data.


A data governance framework also defines cross-functional policies that help streamline data flow issues and increase the value of an organization’s data sources

What exactly is a data governance policy?

In the context of data governance, policies are sets of rules for safeguarding an organization’s data assets. Policies establish roles and responsibilities and decision rights for data including access, disposal, storage, backup, trustworthiness, accountability and protection. Making sure these policies are met should be a consistent process that fosters good use of information through clarity of controls and reduced ambiguity.



To define policies and rules, the business and the IT side of organizations should come together and define used and needed data elements before agreeing on a set of policies concerning the acquisition, management and archiving of data. Policies should not only adhere to laws and general guidelines but also respect ethical issues as well as the company’s philosophy.

Goals and benefits of data governance

The main goals of data governance are adherence to consistent data distribution policies, increased accountability, establishment of standardized systems concerning the use of data as well as educating members of a company in the area of data usage and handling. This entails a number of benefits such as:

• Improved data quality and delivery of trustworthy information


• Making business decisions effective and successful


• Reducing the risk of regulatory fines


• Enabling better risk management and compliance


• Facilitating collaboration not just within but also across organizations and departments


• Compliance with regulations and improved data transparency


• Reduced error rates and elimination of redundant work


When creating a data governance framework for your organization you certainly need to put quite some work and effort into the process. After all designing a framework needs alot of planning as well as the right people and appropriate tools and technologies. However you usually don’t need to start completely from scratch as typically there is some way you company deals with data that can be built upon.


Once an appropriate framework has been defined it creates a process for resolving data issues, enables business users to make decisions based on high quality data and reduces the risk of running into legal problems.




We’re actually working on a solution for data management issues within companies by developing a platform to store and evaluate data collaboratively. You can get more information and updates here.

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