Data Governance

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Although data governance can be defined in various ways, it is ultimately a system of processes, roles, standards, measures, and leadership accountable for information-related processes. Data governance facilitates the efficient and correct use of information, including when, where, and how it is used.

In effect, it refers to how an enterprise meets internal data standards and policies as well as legal requirements to guarantee that data is used with integrity. A firm data governance network is essential to the efficient, compliant, and safe usage of data.

Responsibility of Data Governance

Although the responsibility of data governance implementation falls on an entire enterprise and requires awareness from all employees, certain individuals are key. In fact, large organizations may even create a data governance teams to take on numerous roles like

  • setting goals
  • prioritizing needs
  • creating governance models
  • choose tools
  • gain budget approval
  • handling data-related issues
  • approving data governance policies and standards

Data governance committees are often divided into two groups, one on strategic data governance, and the other on tactical data governance. Whether the data governance committee is divided into groups or not, there are important roles that must be filled. The following is a list of the main roles in a data governance team:

  • Data Owners: Data owners are generally senior managers who dictate an enterprise’s conditions on data and data quality. Data owners make major decisions for the entire organizations, making them accountable for the data as an asset.
  • Data Stewards: As opposed to data owners who are more business-oriented, data stewards are very technical. Also known as data architects, they are often central to governance or IT departments, as they must be knowledgeable about data. Stewards provide definitions and formulas for standardized data elements as well as profiling source system details and data flows between systems. Finally, they ensure that the enterprise meets all data standards.
  • Data Custodian: Data custodians, or data operators, are involved in both the business and technical side of data, including onboarding, updating, and maintaining data assets. In particular, they create and maintain data according to the regulations set by the organization.

Importance of Data Governance

Data governance is essential to the compliance, proper management, and quality maintenance of data. When the quality of data is not high enough it can affect marketing insights, financial planning, and achievement of important KPIs. Ultimately, the benefits of data governance enable organizations to stay agile and compliant.

High-Quality Assurance

Data governance ensures high-quality, clean data. By spreading the responsibility of data governance to a team dedicated to keeping data up to date and clean, data cleansing, updating, and purging occurs consistently. Additionally, strong data governance policies can distinguish between usable information and useless information, maintaining the former and reducing the latter.


Data governance also facilitates faster compliance. For instance, depending on an organization’s needs, both low code and no code options can achieve faster compliance. Data governance software can transform data masking processes, which enables enterprises to rapidly meet compliance standards.

A data governance system can help organizations remain fully compliant with regulatory laws as well like GDPR, HIPPA, PCI-DSS and more.

Data Governance Obstacles

One of the largest obstacles preventing effective data governance is a lack of leadership. Data governance is a responsibility that falls on multiple departments, so a lack of strong governing can cause major disruptions to communication and cohesion. A Chief Data Officer, Chief Information Officer, or senior manager focused on data can lead company-wide decisions regarding data, budget, resources, compliance, etc.

In addition to a leader, a data governance system requires team support. Without a sizable team that understands and manages data usage, the responsibility of data governance falls only on data scientists, resulting in too much work for too few people. A team can help alleviate the pressure and facilitate more effective data governance.

Importance of Data

Sometimes data can be stored in inaccurate systems due to a lack of clarity and understanding of data usage. This can result in a myriad of issues, which can hinder workflows and efficiency. For an enterprise to extract the maximum value from its data, an understanding of how it works is essential.

Data management is a system that institutes policies and procedures to gather data for decision-making. This is distinct from data governance, which is about instituting policies and procedures surrounding the data. If data management processes aren’t thorough and strong, the consequences can include unsecure data, poor visibility into processes, data silos, and weak control over processes.

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