The ultimate guide to data governance

What is Data Governance, and how can it help your organization?

Sam Gillespie
Data Governance Offering Manager, OneTrust
April 12, 2020

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The Data Governance Institute broadly defines data governance as “the exercise of decision-making and authority for data-related matters.”

As we descend from the 30,000 ft definition, data governance can be seen as a collection of processes that enable data stakeholders to create and manage data.

To manage your data effectively, you’ll need a data governance solution that protects the privacy, security, and integrity of the data, while adding value to your business.

Considering the pace at which security frameworks and privacy regulations (such as the alphabet soup of GDPRCCPACPRALGPD, PIPL, ISO, NIST) are evolving, your organization needs robust data governance to not only comply but generate actionable insights as well. 

Throw in the ever-growing volume of data generated each day across departments and it’s clear to see why you need to make data governance a priority. Take a look at the sections below to learn more about data governance and how it can help your organization. 

Top 4 Data Governance Principles

Data Governance relies on a few key principles that ensure checks and balances within your organization. To establish effective implementation, let’s go through four data governance principles your organization can take to turn this daunting task into a rewarding journey.

1. Transparency 

Know what data you have, where it’s located, what it contains, and how it should be protected. 

2. Accountability 

Who is responsible for your data, why do they have access to it, and what are they using it for? Is it compliant? This is the concept of data stewardship, where certain people across departments in your organization take responsibility for data.

3. Data Integrity 

Is your data accurate, relevant, and timely? Does it follow policies? How can your data quality be improved? 

4. Collaboration 

Is there common ground for different disciplines within your organization to view, manage, and operate?

Take a look at what a couple of our trusted partners have to say about their experiences with these principles.

For more information about these data governance principles and how they can help your organization, check out our blog here!

Data Governance Framework

A good Data Governance framework can be summed up in the 5 W’s (and 1 H). 


Who are the data stakeholders, data governance officers, and data stewards responsible for and affected by the data?


What are your goals of data governance, and what metrics do you use to determine success (short-term and long-term) in these initiatives?


When does the data flow from one party or stakeholder to another? When are the cadences in the organization for the movement of data and metadata?


Where is the data stored? Where is it managed? What does the data architecture (the structure of data and data-related resources) look like?


Why are you implementing data governance in your organization? What is your driving mission? 


How is the data going to be modeled? How will analysis, design, testing, maintenance, and data security be baked into these processes to keep them efficient?


Flow chart mapping out the who, what, where, why and how stages of the data governance framework

Pictured Above: The Data Governance Framework as defined by the Data Governance Institute

Data Governance vs. Data Management

Data governance is commonly misunderstood for data management; we’ll break down the main differences here:

Data governance deals with the strategy, policies, and stakeholders involved in your organization. It determines the use and structure of your data for the benefit of your business, with a priority on compliance, security, and ownership of data assets. 

Data management deals with the execution of the framework laid out by your data governance strategy. It focuses on maintaining processes, ensuring data standards, and defining administrative controls.


Infographic comparing data governance to data management and showing their main difference through iconography


4 Steps to Starting Your Data Governance Program

Setting up a data governance program can be daunting. Understanding that this is an ongoing process, and not a project with a completion date is the most important part.

Below are the best steps to take when taking your organization on the data governance journey.

1. Understand your internal data structure

The first step to setting up your data governance program involves understanding your data assets. Discover where your data sits throughout your organization, the different types of data you collect both internally and externally, and who interacts with your data.

2. Leverage AI-driven data interpretation and metadata management 

Automation is a powerful tool. Use it to take your data out of silos and create a centralized, easily searchable data catalog. From here you can apply business rules and assess data quality as well.

3. Govern your data with smart policy management

Define key data policies for your organization that cover rules for access, retention, storage, minimization, and protection. Use these policies to flag violations across your data environment and demonstrate compliance with privacy and security obligations. 

4. Bring it all together with a data governance playbook for your organization

Now that you’ve got your data structure, processes, and policies to enforce your standards in place, it’s time to bring it all together for your data governance program with a clearly defined data governance playbook. 

Make sure that this isn’t set in stone, giving your program room to grow, as data governance is an ever-evolving practice throughout your organization. 

Setting up a data governance program is a rewarding journey! 

The maturity journey starts with simplifying regulatory compliance, slowly evolves to enabling data intelligence and governance, and ends up enabling responsible AI, ensuring data ethics.


On-demand webinar coming soon...


Top 6 Data Governance Best Practices

Once you’ve got your data governance program up and running, there are a few things to keep in mind to make sure it’s operating at its full potential. 

1. Know your data. All your data

All data needs to be considered, including metadata and unstructured data from collaborative tools, SaaS applications, and other shared files.

2. Organize your data

Make sure to clearly define how your organization interprets, classifies, and processes data based on the sensitivity level and policies in place, establishing a single source of truth.

3. Keep up with your data throughout its lifecycle

Manage your data effectively at every stage, with policies on the acquisition, storage, transfer, and disposition of data.

4. Privacy by default and data security

Keep data privacy in mind and ‘bake it in’ when developing processes for your organization’s data, developing checks and balances in your privacy policies.

Implement controls to reduce risk levels while enabling business as usual. Understand your security requirements to avoid conflicting programs and duplicating efforts.

5. Get the business buy-in

Make the business case for data governance to key stakeholders across departments, getting their buy-in to ensure that these policies are circulated and followed throughout key areas of the organization.

6. Have goals and metrics for your data

Keep mechanisms and metrics in place to monitor, evaluate, and improve your processes over time.


Infographic showcasing the top 6 data governance practices


Top 4 Benefits of Data Governance Tools

The best way to take control of your data governance program is to utilize the benefits of a data governance tool or software. This will help you get the most out of your data, reduce manual tasks, and improve efficiency.

A tool like OneTrust’s DataGovernance Solution can help you realize the benefits below.

1. Streamlined business access to data

With an intuitive data catalog across your organization, anyone in your business can find what they’re looking for quickly. Policies can also be monitored, enforced, and improved more effectively.

2. Improved data quality

Your data quality with automated discovery and classification will improve with greater accuracy, less manual work, and human error. 

3. Unified privacy, security & data governance initiatives

Avoid duplicating efforts and enable your business to work together within a single platform. 

4. Automated compliance

Make sure your data is compliant, with automated scripts with defined rules congruent with the latest privacy laws for your region.


On-demand webinar coming soon...


Even after knowing the right principles, frameworksbest practices, and having the right tools, data governance is not a quick fix for any organization.

The best part about the data governance journey is watching your organization evolve.

Setting milestones and goals along the way is the best way to keep your team motivated while having benchmarks to ensure your program is headed in the right direction.

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