Data governance is essential to maintaining the accuracy, availability, integrity, and confidentiality of all data. A data governance policy enables everyone in a company to follow the same standards and procedures, while reducing hacking risks and protecting this valuable asset.
In today’s data-driven world, companies rely on large amounts of data to:
- Make strategic decisions.
- Improve products and services.
- Boost customer satisfaction.
- Grow revenues and cut extraneous costs.
Data governance is particularly important as your company navigates the complexities of the current business environment. Many factors transform how companies do business:
- Regulatory requirements.
- Increased reliance on digital processes.
- An evolving workplace.
- A changing IT landscape.
Data is at the heart of this transformation. A data governance policy and framework build the foundation to allow your company to excel in an ever-shifting landscape.
What is a data governance policy and why do you need one?
A data governance policy is a set of rules that help safeguard data, and establishes standards for its access, use, and integrity. The policies are typically accompanied by standards, which provide more detailed rules for implementation of the policy.
A data governance policy is a critical component of a data governance framework. It guides your company’s decisions about data assets. The framework creates a structure for carrying out data-related activities, and the data governance policy provides guidelines for activities that involve data.
The core purpose of a data governance policy is to recognize that data is a critical asset and must be treated as such. At a high level, the policy promotes a security-focused culture where all stakeholders play an active role in protecting data assets. Although the policy is critical for organizations in highly regulated industries, any businesses that handles sensitive data or relies on data strategically will benefit from a data governance policy.
The components of a data governance policy
While each policy is tailored to an organization’s specific needs, these are some of the typical components included:
Policy purpose: The statement of purpose describes the reason the policy exists and how it supports the organization’s mission or business objectives.
Policy scope: The scope explains who is affected by the data governance policy.
Policy rules: This is the main section that outlines the rules guiding data usage, and access.
Stakeholder roles and responsibilities: Stakeholders range from the data governance body (such as a governance board or committee) and data owners, to data stewards and data users.
Definitions: A glossary includes common terminology referenced in the policy. Some examples might include:
- Data user
Review process: Included in a policy by some organizations, this section describes how the data governance policy is established, reviewed, and updated.
Resources: Any related documents, policies, or regulations are referenced in this section.
Some policies also contain details such as:
- An explanation of the risks related to data.
- Applicable regulations.
- Guiding principles.
Common policy rules to consider for inclusion
Each organization has several foundational policies, or rules, within the data governance policy. These are some of the common elements included in a policy:
Data access and availability: The overarching purpose of this policy is to ensure stakeholders, whether that’s all employees, contractors, specific business units, or other parties, have appropriate access to the information they need. It may include elements such as:
- What is the purpose of the company’s data access.
- Who is granted access.
- Why is access important.
- What are the consequences of improper or unauthorized access.
- How data is classified.
Data usage: This policy ensures that company data is not abused or misused and is used ethically, with consideration for individual privacy, and only as necessary for performing specific roles or functions. The section describes the appropriate purposes and details the common categories of usage, such as:
- Data creation.
- Data updates.
- Read-only access.
- Distribution or sharing outside of the company.
- Consequences of noncompliance, including potential penalties for violations.
Data quality and integrity: Data integrity refers to the trustworthiness of the data throughout its lifecycle, including its validity, reliability, and accuracy. The integrity of data can be compromised by internal processes such as human error and unintended transfers, and external forces such as security incidents. The policy should describe who is responsible for ensuring that data is correct and how it should be validated.
Data usability and integration: Sometimes grouped together with the data integrity policy, data integration defines the consolidation of data from multiple sources and provides a unified view across multiple information systems. The data integration policy ensures both the availability of the data and its fitness for use, and should include provisions for structuring the data correctly with proper labeling so it can be retrieved.
Data security: While your organization may have a comprehensive data security policy and framework, including a high-level element in the data governance policy helps reinforce some of these suggested safeguards. Ultimately, security impacts data:
Some additional elements to include in the policy are:
- Data inventory.
- Records management.
- Data content management.
13 steps to creating a data governance policy
Building a data governance policy doesn’t take place in a vacuum. This process should be part of a bigger effort to implement a data governance plan or to create a data governance framework. Organizations typically have some of the components in place for a solid policy, such as an identified mission and purpose.
If your data governance policy creation is a standalone exercise, here are the recommended steps:
- Assess your current data-related challenges and constraints and the state of existing data governance activities.
- Understand the business prerequisites and challenges that are driving the need for a policy.
- Establish the business case for a policy and make sure you have buy-in from top leadership.
- Assemble your data governance team and define their responsibilities. Not all the stakeholders will be actively involved in building the policy; however, all should be empowered to provide input and play a role in the process.
- Identify the key stakeholders and decision-makers from across different business units and functions.
- Collect the stakeholders’ input, including data challenges, expectations for the policy, and their needs. This can be achieved through a combination of formal and informal activities.
- Understand the impacts of the data governance policy on the different stakeholder categories. This will help you with tactical execution, including how to motivate stakeholders’ participation in adopting and complying with the policy.
- Keep the shared vision in mind when you create your initial draft. Get feedback from stakeholders and decision-makers and iterate.
- Define the metrics you can use to measure implementation success and policy performance. Plan for both short-term and long-term measurements and assign specific roles or individuals to this task.
- Create an organization-wide rollout plan. This should include a communication plan, as well as resources for training and education as necessary.
- Discuss potential technology needs, and what existing IT tools you can repurpose for supporting and enforcing the new data governance policy.
- Measure results and share quick wins with all the stakeholders. This reinforces the importance of the policy and promotes continuous buy-in.
- Review the policy regularly to keep it relevant, current, and effective.
Data governance combines people, processes, and tools. For your data governance policy to be effective, you need to support it with the right technology. In the current business environment that combines on-premises and cloud systems, manual processes and outdated technologies can create inconsistent policy adherence and enforcement.
SailPoint File Access Manager helps you get visibility and control over you unstructured data. You can quickly and compliantly discover sensitive information, such as PII, PHI, and PCI data and classify and secure it in accordance with regulations such as GDPR, CCPA, and HIPAA. In addition, File Access Manger helps to identify and elect data owners and alert them to remediate risk exposures and manage data access requests and reviews.
To learn more, please see our File Access Manager webpage.
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