Indeed, the information extracted from Data Science, AI, and Analytics practices is diverse and valuable. Still, its integrity 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 that, in addition to ensuring security, helps to extract value from all data collected and stored by the business.
First, 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. Thus, it is a function within data management, distinguished from the other parts – data architecture, data integration, and data quality, among others – by focusing on supervision rather than execution. Therefore, it is a fundamental practice; without it, technology projects could be affected, as they would take longer to complete, their value would decrease, costs would increase, and so would risks.
“Businesses that successfully organize the who, what, how, when, where and why of data not only ensure security but also manage to extract value from all information collected and stored across the business.”
In this way, the data governance framework will guide you through the steps you should follow to implement data governance in your organization. It will help to establish data standards and delegate tasks and responsibilities required within the organization and those directed to the people related to the organization. In other words, to put everyone on the same page. Different institutions develop several frameworks. For 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 starting a data management program. It involves aligning concepts and identifying the organization’s strengths in data management.
While the DAMA focuses on the what, the DGI Framework also covers the why. The purpose is to have cleaner, clearer, and more reliable data since they went through control that ensures their clarity and integrity.
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 to consider data governance from the beginning. This way, establishing rules would avoid dealing with disobedience, ambiguities, and other issues that may appear during the use of data.
The Data Governance Framework you choose must fit 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. In addition, the steps to build the Data Governance Framework must be constantly reviewed and updated, if necessary.
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