Who controls your data? Understanding data ownership

Data ownership refers to the accountability and responsibility within an organization for managing, controlling, and safeguarding data.

It involves defining who has the authority to manipulate data and dictate how it’s accessed and used across the company. Data ownership is essential for maintaining the quality and integrity of your data, while remaining secure and compliant.

Data owner vs. data steward vs. data custodian 

When it comes to data governance, the data owner, data steward, and data custodian play distinct but interconnected roles in managing and protecting data. Between them, they ensure data is kept securely, compliantly, and with its integrity intact.

Data owner

The data owner has the ultimate authority over data assets. They are typically a senior-level executive or department head.

They are responsible for defining policies, access controls, and compliance requirements relating to the data.

Data steward

The data steward enforces data policies to ensure they are accurate and consistent and adhere to the governance rules. Data stewards work closely with data owners and data custodians.

Data custodian

Data custodians are responsible for the technical aspects of data storage, security, and infrastructure. These duties usually fall under the remit of IT teams or database administrators.

Together, these roles form a hierarchy that is the essential structure for managing and protecting data.

Here’s an overview of their responsibilities and key relationships:

• Data owner
  • Defines policies and grants access
  • Oversees data stewards and custodians
• Data stewards
  • Maintains data accuracy and compliance
  • Works with data owners to enforce policies
• Data custodians
  • Manages storage and security
  • Implements data owner’s policies and data steward’s requirements

The importance of data ownership

Data ownership clearly defines who owns (and is responsible for) data. This makes it a vital component of modern data governance policies within any organization.

Upwards of 95% of organizations see negative impacts from poor data quality. And although nearly all companies (98%) use data to improve customer experience, most (89%) concede that they find managing their data challenging. 

This is where data ownership comes in. Here are five key reasons why data ownership is considered essential.

1. Strengthens data governance framework

The more well-defined data ownership is within an organization, the better it can be used to enforce its governance model policies, control access, and ensure compliance with regulations like GDPR or HIPAA.

As senior managers are responsible for setting the security protocols, they are able to significantly reduce the risk of breaches and prevent unauthorized access.

2. Improves accuracy and consistency

Data owners work with stewards and custodians to maintain data integrity. It is these clearly assigned ownerships that enable information to remain accurate, up-to-date, and consistently formatted across all business systems.

This, in turn, makes the company’s analytics and reporting functions much more reliable indicators of performance.

3. Improves collaboration and efficiency

In companies where ownership roles are clearly identified, team members know exactly who to contact should any data-related issues arise.

This clarity can create a more efficient data management process because it helps to streamline workflows, reducing the doubling up of effort and increasing collaboration between departments.

4. Builds accountability and trust

Clarifying data ownership and accountability within an organization allocates responsibility. Team members understand who is responsible for what.

Empowering them in this way ensures data is handled ethically and securely. Also, due to clearer accountability, user trust in the quality of the data increases, benefitting both internal teams and external stakeholders.

5. Creates better decision-making

The more reliable and well-governed your company’s data is, the better equipped you are to make informed business decisions.

By clearly establishing their ownership, organizations can use their data more effectively, minimizing potential for errors and maximizing any opportunities for strategic growth, thanks to the more salient insights they will get.

What are the three main data ownership rights?

Data ownership comes with specific rights that determine how data can be accessed, modified and shared within an organization. Here are the three main data ownership rights.

Access control

Data owners define which employees can view (read), change (edit), or fully manage (admin) data.

In the context of a company’s CRM function, this might mean that sales staff may have read access to customer data, while managers can edit records, and administrators control overall settings.

Modification control

Owners can modify or delete data when necessary, which typically includes anonymizing personal data for privacy compliance or erasing outdated records.

This might be applied in situations where, for example, a customer requests their personal data be erased from an online retailer’s database (under the regulations of GDPR).

Distribution control

Data owners decide how and where data can be shared or monetized, potentially through internal data sharing between departments or selling anonymized data for market research.

For example, a streaming service may sell viewing trend information to advertisers while ensuring that data user privacy is not compromised.

How does data ownership work?

Data ownership is usually outlined and assigned through a structured process similar to this:

Data owner → Sets rules and access → Users follow guidelines → IT ensures data quality and security → Regular reviews and updates

Here’s a more in-depth overview of how it works:

1. Identify the data owner

The first thing a company needs to do is assign ownership of specific data to a person, team, or department.

Usually, the person responsible for managing and securing the data is a department head, IT manager, or business leader.

2. Define access and permissions

The owner decides who can access the data and what they can do with it, normally by breaking down permissions into three sections:

• Read (view only)
• Edit (modify data)
• Admin (full control)

One example of this could apply to a company’s financial records, which might see accountants having edit access granted to them, while executives may be given read-only permissions.

3. Establish rules for use

The data owner sets guidelines for how the data can be used, stored, and shared, which helps to maintain compliance with regulations like GDPR or HIPAA.

4. Ensure compliance and security  

The data owner works with IT and stewards to safeguard data from breaches and ensure it meets all the required legal and industry standards.

5. Monitor and update

Data ownership is not a set-and-forget process – it must be regularly reviewed to ensure permissions, rules, and security measures remain current.

How companies use data ownership in different industries

Data ownership is an integral business function vital to ensuring security, compliance, and efficiency for organizations, no matter the business environment. Let’s take a look at how data ownership is successfully implemented across five key industries.

1. Healthcare

Hospitals and clinics handle sensitive patient records. Data ownership ensures that only authorized personnel can access or update medical histories.

This serves to reduce errors, and it protects a patient’s privacy under laws like HIPAA.

2. Finance

Banks and financial institutions rely on strict data ownership, as it helps them better monitor transactions, prevent fraud, and comply with regulations like GDPR.

Additionally, if clear ownership is outlined within a company, it will ensure more accurate reporting takes place, helping to fortify customer data management in an even more secure way.

3. eCommerce

Most retailers use customer data to provide personalized recommendations to customers and tailor marketing campaigns.

Taking steps to put proper ownership in place allows businesses to securely analyze shopping behavior while remaining compliant with data protection laws.

4. Manufacturing

Manufacturers manage vast amounts of supplier and production data, so it’s important they have good data ownership processes in place.

Effective data ownership helps them to streamline their operations, predominantly by ensuring materials are tracked accurately. This also helps them to reduce waste and improve overall efficiency.

5. Technology

Tech companies need to have proper data ownership in place because they manage vast digital infrastructures that need to ensure that only authorized users can access sensitive system data.

This helps to prevent breaches and maintain a justified level of customer and stakeholder trust in their operations.

5 steps for implementing effective data ownership protocols

Now that you know what data ownership is, why it is important, and how it works, let’s take a look at five key steps for implementing effective data ownership protocols. Here’s a step-by-step process outlining a clear path for achieving effective data ownership.

Step 1: Identify and appoint data owners

Start by pinpointing which data assets need oversight. Assign clear ownership of them to specific individuals, teams, or departments.

Ideally, data owners should have the expertise and authority to manage these assets. It’s important to get this right. Clearly assigning responsibility establishes accountability for data management and goes a long way toward reducing ambiguity.

Step 2: Define roles and responsibilities

After you’ve identified the responsibilities of data owners, it’s time to assign and clearly delineate the roles of data stewardship and custodians.

It’s vital to specify who is responsible for policy enforcement, data quality assurance, and technical security and compliance measures. Outlining these responsibilities will ensure that everyone understands their duties.

This will help reduce any risks associated with data mismanagement and help team members collaborate more smoothly with each other.

Step 3: Develop and document data policies

With all roles assigned, shift your attention to creating comprehensive guidelines that cover aspects such as access control, modification rights, and distribution rules.

Document procedures for reading, editing, anonymizing, or erasing data, and establish protocols for data collaboration.

Well-documented policies will provide an excellent reference point for compliance, ensuring all data handling practices are compliant with regulatory standards.

Step 4: Implement security and access controls

Next, deploy technical measures to safeguard your data, such as role-based access control systems, encryption, and secure authentication.

Make sure these systems reflect the defined ownership policies you have put in place and allow for the regular monitoring of access and modifications.

The stronger your security measures, the better they can prevent unauthorized access or data breaches from occurring.

Step 5: Monitor, audit, and update regularly

As data environments and regulatory requirements evolve, your ownership requirements and data management practices must remain current and effective.

It’s a good idea to review your data ownership practices on a regular basis to identify ways to improve them, such as by addressing gaps or non-compliance issues.

4 best practice tips for data ownership

When devising a data ownership strategy, here are four best practices to follow.

1. Define roles clearly

If team members aren’t sure about what level of data ownership they have, it can result in confusion, miscommunication, and unauthorized access to data.

To avoid this, it’s essential to clearly define and assign ownership roles and make sure each dataset has a responsible owner who understands their duties.

2. Implement strict access controls

Unauthorized access to sensitive data can cause a range of issues, including increased security risks and inappropriate changes to it.

The best way organizations can protect themselves from these eventualities is to implement strict access controls that use role-based permissions, which limit who can view, edit, or manage data.

3. Standardize data policies

If data is handled inconsistently by staff, compliance issues can result, which may result in significant damage to your company’s reputation.

For this reason, implementing standardized data policies across the business as a whole will ensure that everyone is following the same guidelines for the storage, sharing, and deletion of data.

 4. Create clear accountability

Errors in data can occur when changes are made without people noticing.

This is often due to a lack of accountability, which can be easily addressed by enabling owners to track data changes via audit logs, more easily identifying potential issues.

Summing up

Data ownership is an essential business function. The more clearly your organization can define ownership roles, set access controls, and implement structured protocols, the less susceptible you’ll be to data misuse.

RecordPoint can help you master data ownership, while also strengthening the security of your business, enabling it to maintain regulatory compliance and empowering employees to make more informed decisions. 

FAQs 

1. What is the importance of data ownership?

Data ownership is important because it creates accountability and security within an organization's data ecosystem.

By assigning data ownership to specific employees, businesses ensure data security, improved data quality, and reliable data access is significantly enhanced.

This process also helps with defining data roles and responsibilities, which leads to better data governance.

2. How does data ownership improve AI models?

AI models rely on well-maintained data quality and structured data flows to operate effectively. 

Therefore, by implementing data ownership, companies ensure that data engineers can access reliable data sets, which subsequently reduces errors and improves the accuracy of the model.

Furthermore, by establishing data governance, they can also enhance their data classification and data observability frameworks to create better artificial intelligence (AI) performance.

3. What are common challenges in assigning data ownership?

There are a few common challenges associated with data ownership, including data silos, resistance to change, and unclear key responsibilities of data teams.

However, implementing a strong data strategy that includes a data catalog and a glossary helps overcome these issues by boosting data democratization and defining data sources.