Data governance framework

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Although the information extracted from data in Data Science, AI and Analytics practices is diverse and useful, its veracity could be affected if the data used is not treated according to a data governance framework. The data governance framework is precisely a framework for data management which, in addition to ensuring security, helps to extract value from all data collected and stored by the business. First of all, it should be mentioned that data governance is an exercise of planning, monitoring and application of data management that involves the best principles and practices. In this way, it is a function within data management, which is distinguished from the other functions – data architecture, data integration, data quality, among others – by focusing on supervision and not execution. Therefore, it is a fundamental practice without which technology projects could be affected, as they would take longer to complete, lower their value, increase costs and increase risks.

Organizations that successfully organize the who, what, how, when, when, where and why of data not only ensure security, but also extract value from all information collected and stored across the business.

In this sense, the data governance framework will guide you to know what steps you should follow in order to implement data governance in your organization. It will help to establish data standards and delegate tasks and responsibilities required within the organization as well as those directed to the actors related to the organization, that is, to put everyone on the same page. There are several frameworks developed by different institutions, as an example we can mention the DGI Data Governance Framework and the one proposed by DAMA in its DMBok.

The Data Governance Institute (DGI) proposes to address the essential questions of why, who, how, what, when and how data is used. On the other hand, there is the DAMA, which talks about the path to start a data management program. It involves aligning concepts, identifying the organization’s strengths in data management. While the DAMA focuses on the what, the DGI Framework also covers the why. In any case, the purpose is to have cleaner, clearer and more reliable data, since they went through a control that ensures their clarity and veracity.

Ideally all organizations that handle data should be concerned about implementing data governance in their planning structure.

Does your organization need a Data Governance framework?

Ideally, all organizations that handle data should be concerned about implementing data governance in their planning structure. Although many are concerned about it until they are faced with data management complications, it is recommended that data governance be taken into account from the outset. Thus, establishing rules would avoid dealing with disobedience, ambiguities and other issues that may arise during the use of data. It is important that the Data Governance Framework you choose fits your organization and business objectives.

Allocating a budget for data governance is not enough; data governance should be seen as a capability to be developed gradually by the organization. Furthermore, the steps taken in the construction of the Data Governance Framework must be constantly reviewed and updated, if necessary.

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