Data Governance - 10 Best Practices and Use Cases

Data Governance - 10 Best Practices and Use Cases

What is data governance?

Data governance is a critical system of policies and processes organizations use to securely and responsibly manage their enterprise data. By implementing a comprehensive data governance framework, organizations can ensure that their data is accurate, secure, and compliant with any applicable regional laws and data privacy regulations. This type of framework can also help organizations leverage their data to make better decisions, drive innovation, and improve their overall performance.

This blog covers the importance of data governance, its benefits, and how to set up a successful data governance program. We will also go over the ten best practices for data governance and how to measure its success. Lastly, we will discuss how Protecto can help your organization implement a robust data governance framework.

Data Governance Policy Examples

When it comes to drafting an effective Data Governance policy, following the Data Protection policies imposed by the Government plays a huge role in whether the Data will be protected or not, and the company avoids persecution from the Government along the way.

Some of the examples of Freely available Data Governance Policies are:

University of Nevada Las Vegas (UNLV) 

This Data Governance policy drafted by the UNLV specifies in detail the ways to store and document access usage, data usage and data integrity. Implementing this policy into your data will prove very useful.

Oklahoma Office of Management & Enterprise Services

The document template provided by the Oklahoma Office of Management provides a detailed blueprint of the data stored and its groupings. There are certain criteria to be met when deciding which groups to put under this policy.

New Hampshire Department of Education

In this policy, datasets can go deep into the job clearance and job type of individuals. These datasets play a huge role in discerning what type of job will garner the most scope in the future.

Brandeis University

There is a critical first step to be followed in this specific data governance policy from Brandeis University. This step is to identify and note all the data sources from which the organization can be traced back. Then a data trustee is assigned to each source of data where they can filter and view the raw data from different sources.

University of New South Wales (UNSW) Sydney

They have split data governance into 2 different policies. One is for businesses to follow and the other is for research and development projects. Both have different data governance policies they need to follow.

There are many policies and rules implemented for fair data governance. However, not all policies can be followed all the time. There are a few difficulties that can be faced while implementing Data Governance policies to existing data.

Importance of Data Governance

Data governance is essential for organizations that want to make the most of their data, ensure data accuracy and security, and remain compliant with any applicable laws and regulations. A well-designed data governance framework can help organizations use their data more effectively, protect it from misuse and security threats, and ensure that it is compliant with all applicable laws and regulations.

Data governance can also help organizations uncover insights that can help them optimize their operations, improve customer experience, and create new growth opportunities. By creating a data governance framework that enables data to be used securely and responsibly, organizations can use their data more effectively and make more informed decisions.

Benefits of Data Governance

There are several benefits that organizations can gain by implementing a data governance framework, including—

  • Enhanced data accuracy and reliability
  • Improved data security
  • Increased compliance with applicable laws and regulations
  • Improved customer satisfaction
  • Optimized operational efficiency
  • Improved decision-making and innovation

At the same time, data governance can help organizations reduce costs associated with data security and compliance, as well as reduce the risk of data breaches and other security threats.

Data Governance Challenges

Many challenges can be encountered while implementing Data Governance policies. Here are a few of those.

Data Silos

Data Silos are a type of data storage where a singular group has access to the data and no one else has access to it. This creates a power imbalance and a high chance of authoritarian data handling in the future.

Data Quality

Even though the whole world depends on data, the quality of it before all the polishing remains questionable at best. Even today many enterprises struggle to acquire better data quality from which meaningful statistics can be made.

Poor Leadership

A good leader can make or break a company. The same concept applies to Data Governance too. If the leader doesn’t follow Data Governance policies, they might be inching closer to trouble and severe consequences.

Limited Resources

There aren’t infinite computational resources. Dwindling resources also make it difficult to follow Data Governance policies if they don’t have enough resources to arrange and compute the data in such a way.

Lack of Control

Another challenge with implementing Data Governance policies is that it might be very restrictive to change along with a lot of things. Updating privacy policies based on the tech climate is very important.

Data Management vs Data Governance

While both Data Management and Data Governance have the same goal, they have some glaring differences between each other.

Data Management vs Data Governance

In short, we can say that Data Governance is a set of procedures and rules to be followed while storing data and Data Management are a set of techniques developed with Policies in mind and implemented on the data.

Data Governance Principles

There are many Principles to be followed when implementing Data Governance techniques to the dataset. They are:


It is important for those to take accountability and ownership over different streams of data. This ensures equal distribution of power and no single person knows the whole data structure.


The data owners need to stay true to themselves and not expose their dataset to any weaknesses or cyber attacks from malicious users.


Another principle of Data Governance is Data Transparency on all fronts. All data owners and shareholders need to be aware of any new policies/changes instead of just the top brass.

Manage Changes

In this digital age, few things remain constant in cyberspace. The data governance policies should also reflect these changes rather than being a monolith of the past.

Data Security

Last, but not the least, Data Security is paramount in Data Governance. Ensuring Data Security and protection is the heart and soul of the Data Governance policies.

Data Governance Roles

There are a plethora of roles given to those related or indirectly related to the data. Some of them are:

Data Stewards

These are the people responsible for managing, and storing assets within the organization.

Data Custodians

These are the people who protect and maintain data. They devise cybersecurity measures to protect data from malicious users.

Data Users

These people leverage the data from the dataset and use it to meet organisational goals and procure insights from them.

Data Governance Lead

These are the people who are responsible for enacting and ensuring all the Data Governance policies are strictly followed and implemented.

Data Governance Committee

These are the people who approve and direct the Data Governor and their team to follow certain rules. They are an oversight committee built to ensure the highest standard of Data Governance policies.

Data governance use cases

There are many use cases in which Data Governance policies are followed. In different industries, Data Governance policies are implemented. Some of the industry use cases are seen below.

Data Governance Financial Services

In the finance sector, a robust Data Governance Policy must be implemented and maintained. People’s financial credit score is very private and leaking any information would result in severe consequences.

Protecto provides you assurance to protect your financial data to the highest data governance standard. They follow GDPR standards.

Data Governance Cloud Services

Most, if not all of our data are stored in cloud storage since the data has become impossibly huge to be stored and computed locally. But, storing sensitive data such as health information, financial details and so on in the cloud would be a cause for concern. Hence, implementing Data Governance policies and checking if the cloud services work according to the policies is also important.

Protecto provides the best solution with their agentless RAG solution which can be integrated into your cloud service at a low cost while ensuring that your data is stored and follows all Data Governance policies. 

Data Governance Healthcare

With the introduction of the EHR (Electronic Health Record), even healthcare data is stored online. Healthcare data is one of the most sensitive data out there, next to financial data. Healthcare data is necessary to go through case studies and research for better solutions for diseases previously thought as incurable.

Protecto assures the best type of data pseudonymization and guarantees that all data are stored in such a way that they comply with HIPAA policies.

Data Governance IT

Many MNC companies store data from different continents, be it Asia, Europe or North America. All of these continents follow different Data Governance policies and restrict certain data where other places may allow it. It all depends on how companies balance it properly.

Protecto offers cloud services and intelligent tokenization techniques from which they can secure your data in a way that you need not worry about violating any Data Governance policy.

10 Data Governance Best Practices

Establish a data governance strategy:

Organizations should create a data governance strategy that outlines the objectives, principles, and processes of the data governance program. This helps create a clear roadmap for the data governance program and ensures that it aligns with the overall organizational goals.

Establish data governance policies and procedures:

Organizations should create policies and procedures that define how data should be managed and used. This helps take care that data is managed in a secure, consistent, and compliant manner.

Establish data governance roles and responsibilities:

Organizations should clearly define the roles and responsibilities of stakeholders involved in the data governance program, such as data stewards, data owners, and data users. This will ensure that all parties are aware of their obligations and expectations regarding the data governance program.

Establish data governance standards:

Organizations should create standards that define how data should be organized, stored, and used. This makes sure that all data is stored according to best practices and that it is used appropriately.

Establish data governance metrics:

Organizations should establish metrics to measure the success of the data governance program and make adjustments as needed. This will allow them to track the effectiveness of the data governance program and make any necessary changes to ensure that the program is functioning as intended.

Establish data governance tools:

Organizations should select and implement tools to support the data governance program, such as data quality management tools, data management tools, and data security tools. These tools will help ensure that the data governance program is managed and monitored effectively and efficiently.

Establish data governance processes:

Organizations should establish processes for managing the data governance program, such as data access requests, data cleansing, and data archiving. This will help establish that the data governance program is operating in an organized and efficient manner.

Establish data governance risk management:

Organizations should create a risk management plan to identify and mitigate potential risks associated with their data. This will help the organization make sure that the data is protected and that any risks are addressed in a timely manner.

Establish data governance auditing:

Organizations should establish auditing processes to ensure that the data governance program is operating in accordance with the established policies and procedures. This will guarantee that the data governance program functions as it should and that all stakeholders are held accountable for their actions.

Establish data governance training:

Organizations should provide training to all stakeholders involved in the data governance program to ensure that they understand the policies, procedures, and standards associated with it. This will ensure that everyone involved is aware of their roles and responsibilities and is able to properly manage and use the data.

Suggested Read: Shadow AI: The Emerging, Invisible Problem Putting Your Company's Data at Risk

5 best Data Governance KPIs

There are many KPIs (Key Performance Indicators) used to evaluate the success of a certain Data Governance policy. Out of the many indicators, we will go through the five major KPIs for Data Governance policies.

Quality Score of Data

Data Quality plays a big role in Data Governance. The higher the quality of the data, the better the predictions, analysis and insights can be made.

Percentage of Data Availability

The Availability of data plays a huge role in making or breaking a data governance policy. Instead of focusing on irrelevant features which have little to no data points, policies can be made to regulate the more popular features out there.

Rate of Data Incidents

The effectiveness of a Data Governance policy depends on how it has prevented the number of data leaks, cyber-attacks or even mishandling of data.

Data stewardship activity

The Data Governance policy also checks the amount of maintenance and storage of data by data stewards. If it lessens their burden, they can focus on more important work. Hence, it is a win-win situation.

Compliance with Data Governance Policies

Another key indicator of Data Governance Policy success is to see how consistently it is employed. Is it easy to employ it? Does it improve data security? Does it reduce cyber-attacks? All of these questions are answered with this indicator.

Data Governance Audit

Audits for Data Governance are implemented on every piece of data used for analysis. This means that there is a rigorous checking of data points to ensure all policies are followed properly.

How Do You Measure the Success of a Data Governance Program?

In order to measure the success of their data governance program, organizations should examine a wide range of metrics, including data accuracy, data security, compliance, customer satisfaction, operational efficiency, and decision-making and innovation. These metrics should be closely monitored on a regular basis to ensure that the data governance program is functioning as intended.

Additionally, organizations should consider other indicators of success, such as the efficiency with which data is being used to drive business decisions, the speed at which new products are being created and launched, and the overall impact that the data governance program is having on customer experience. By looking at all of these factors, organizations can get a clear picture of how their data governance program is performing and make adjustments as needed to ensure that it continues to be effective.

How Protecto Can Help Your Organization Build a Strong Data Governance Framework

Protecto can help your organization build a strong data governance framework by providing a comprehensive suite of tools and services. We offer a range of solutions such as data privacy, data security, and data usage analytics. Our team of experts can also help you develop and implement a data governance roadmap that outlines the steps needed to achieve your goals.

With Protecto, you can ensure that your data is secure, compliant, and used in the most effective way possible. Additionally, we also provide insights into how your data can be used to drive innovation and create new opportunities for growth. Contact us to find out how we can help with building a framework for your data privacy, security, and governance needs.

Download Example (1000 Synthetic Data) for testing

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