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Data governance principles: 4 best practices

Discovery and classification are necessary in data governance, but clarity and accountability are at the root of collaboration

Sam Curcuruto
Sr. Product Marketing Manager
October 5, 2023

Woman making notes on a whiteboard during a brainstorming session.

With the amount of data and metadata aggregated and collected by companies growing by the day, you need to make sure that it’s managed effectively.  

Successful data governance relies on a few governance principles that require organizational buy-in from top to bottom. Let’s take a look at them.

 

Transparency 

Having clarity on what data assets you have and spreading this knowledge across your organization and customers is of utmost importance for your data governance framework. Transparency and trust go hand in hand.   

To have your employees and customers buy into your data governance policies, you need to build trust by being transparent about the data you collect, the purpose of the data, where it’s stored, and whom it interacts with. 

  • Data Governance Goal: To foster trust in your organization’s data policies, both internally and externally. 

 

Accountability 

“It’s not my responsibility.” 

You never want to hear those words regarding data in your company. The concept of data stewardship comes into play here, where individuals become ‘stewards’ for data stored in different places across your organization. This involves moving away from the traditional viewpoint on data, which generally had the IT function as the decision-making body for data assets and data management.  

Governing unstructured data requires discovery and classification that goes beyond simple metadata. Learn more here

Instead, set data definitions, look to identify key stakeholders across different departments, and establish them as data stewards responsible for the data that’s relevant to their department.  

  • Data Governance Goal: Ensure that there are no ‘data gaps’ in your organization where nobody is responsible.  

 

Integrity 

This can be summed up with “How good is your data?”. Making sure your data catalog is accurate, relevant, timely, and compliant with policies and regulations is critical in ensuring successful data governance.  

Integrity also comes into play when dealing with how stakeholders discuss the impacts of decisions on enterprise data, and being honest regardless of the circumstances involved. The two sides of the integrity coin are truthfulness regarding the effects of data processes and maintaining the highest possible data quality. This becomes even more critical as we use data to train AI models—we need to know the data has integrity.

  • Data Governance Goal: Establish a culture of honesty around data policies and set processes to ensure data quality. 

 

Collaboration 

We’ve all heard “teamwork makes the dream work.” Departments within your company should have the opportunity to discuss the best practices to deal with data in different parts of the organization.  

Setting effective data standards, and not idealistic ones, can only happen through inter-department collaboration. An extension of this data governance principle is to enable access to data through an intuitive catalog.  

  • Data Governance Goal: Establish a Data Governance Council to set effective standards and metrics, and enable accessibility throughout your organization.   

These four principles are the pillars upon which any effective data governance program is built. When they come together, it ensures a strong foundation for your data governance policies and processes as you enforce them throughout your organization.

 

How OneTrust Data Discovery helps

OneTrust Data Discovery serves as a valuable tool for Chief Data Officers, Chief Privacy Officers, and Chief Information Security Officers alike. Enhanced unstructured data discovery capabilities help find unstructured data across common shared-use applications as well as understanding the compliance obligations attached to the sensitive or personal information found within these files.  

OneTrust’s enhanced unstructured data discovery capabilities utilizes advanced machine learning-based classification to give users a clearer view into at-risk, sensitive, or personal data down to the individual data element level and automatically populate data maps to help maintain compliance with privacy and security regulations. Moreover, OneTrust Data Discovery adds further context to your data by helping you understand who has access and that the right level of access is implemented alongside applicable governance policies.  

OneTrust Data Discovery automatically populates data inventories, giving governance teams a clear, centralized view of their data, helping with compliance obligations, retention periods, and access controls.

Learn more about OneTrust Data Discovery tools and Data Governance by requesting a demo.


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