Data Governance vs Information Governance: What's Your Priority?

Last Updated on: June 16th, 2023, Published on: May 18th, 2023
header image

Share this article

Data governance is a set of procedures and guidelines that detail how data is to be properly managed, accessed, and used. On the other hand, information governance is the framework for handling information in a way that supports an organization’s immediate and future regulatory, legal, risk, environmental, and operational requirements.

In a nutshell, while data governance is about managing data, information governance is about managing all kinds of information in an organization.

In this blog, we will understand the relationship and differences between them, how to approach and implement them.

Let’s dive in!

Table of contents

  1. What is the difference between data governance and information governance?
  2. Approaching and implementing data governance and information governance
  3. When should you consider data governance, information governance, or both?
  4. The interrelationship and differences between data governance and information governance: A tabular view
  5. Practical examples of data governance and information governance in action
  6. Bringing it all together
  7. Data governance and Information governance: Related reads

What is the difference between data governance and information governance?

Data governance provides a set of procedures and a plan to execute those procedures that ensures that important data assets are formally managed throughout the enterprise. It encompasses the people, processes, and IT required to create consistent and proper handling of an organization’s data across the business enterprise. Key elements include data quality, data integration, data privacy, data strategy, and data operations.

Information governance is a broader category that includes data governance within its framework. It involves the principles, policies, and procedures around the lifecycle of all information, whether it is structured data, unstructured data, or paper documents. So, while data governance is about managing data, information governance is about managing all kinds of information in an organization.

Here’s how you might think about both:

Data governance explained

You want to make sure that the right users have access to the right data, ensuring data security and privacy. You also want to maintain high data quality by setting and enforcing standards for data entry, processing, and usage.

This might include things like creating a data dictionary, implementing data access controls, setting up data stewardship teams, and using data quality tools to monitor and improve the quality of your data.

Information governance explained

At the same time, you also need to manage all other types of information in your organization, not just structured data. This could include emails, documents, images, and other forms of unstructured data.

You’ll need to think about how this information is created, stored, used, archived, and eventually destroyed, keeping in mind all relevant legal, regulatory, and business requirements. This might involve things like setting up a document management system, implementing information access controls, and creating policies for information lifecycle management.

To sum up, while data governance deals specifically with the handling of data, information governance is a more comprehensive framework that includes the handling of all forms of information. Both are essential for managing information risks and enabling business efficiency and effectiveness.

How to approach and implement data governance and information governance?

Here are some guidelines for approaching and implementing both data governance and information governance in your organization.

First up, let us see how to approach and implement data governance.

Data governance - How to approach and implement it?

  1. Establish a data governance council
  2. Identify critical data elements
  3. Define data quality metrics
  4. Create a data dictionary and catalog
  5. Implement data stewardship
  6. Develop and implement data policies and procedures

Let us look into each of the above approaches in detail:

1. Establish a data governance council

This team should be cross-functional and include representatives from different departments. The council will establish and oversee the data governance framework, policies, and standards.

2. Identify critical data elements

Determine which data elements are crucial to your operations and decision-making. These might include customer data, financial data, operational data, etc.

3. Define data quality metrics

Define what data quality means for your organization and create metrics to measure it.

4. Create a data dictionary and catalog

A data dictionary and a data catalog will provide everyone with a clear understanding of what data is available, what it means, where it is located, and who is responsible for it.

5. Implement data stewardship

Assign data stewards who will be responsible for the quality, integrity, and privacy of the data.

6. Develop and implement data policies and procedures

These policies might cover data privacy, data security, data usage, data archiving, and more.

Next, let’s see how to approach and implement information governance.

Information governance - How to approach and implement it?

  1. Establish an information governance committee
  2. Carry out an information audit
  3. Develop an information lifecycle management (ILM) policy
  4. Implement information security measures
  5. Create retention and disposal schedules

Let us look into each of the above approaches in detail:

1. Establish an information governance committee

This team, like the data governance council, should be cross-functional and represent different departments. They will establish and oversee the information governance framework, policies, and standards.

2. Carry out an information audit

Understand what information you have, where it’s stored, who owns it, and how it’s currently managed.

3. Develop an information lifecycle management (ILM) policy

This policy should cover how information is created, used, stored, archived, and destroyed.

4. Implement information security measures

Protect your information from unauthorized access, disclosure, modification, or destruction.

5. Create retention and disposal schedules

Determine how long different types of information need to be kept and when they can be disposed of.

When should you consider data governance, information governance, or both?

In this section, we will understand when to consider data governance, information governance, or a combination of both for effective data and information management strategies.

Consider implementing data governance when:

  1. You are experiencing data quality issues that are impacting decision-making or operations.
  2. There are concerns about data privacy or data security.
  3. You are struggling to integrate data from different systems or departments.

Consider implementing information governance when:

  1. You are dealing with large amounts of unstructured data (like emails or documents) that are difficult to manage.
  2. There are concerns about compliance with legal or regulatory requirements related to information management.
  3. You are facing issues with information security or privacy that extend beyond structured data.

In most cases, organizations will benefit from implementing both data governance and information governance. While there may be some overlap, each covers important aspects of managing and using data and information that the other does not.

By implementing both, you can ensure that all of your data and information is managed effectively, securely, and in compliance with all relevant requirements.

The interrelationship and differences between data governance and information governance: A tabular view

In this section of the blog, we’ll explore the relationship and differences between data governance and information governance using a simple table:

 Data GovernanceInformation Governance
DefinitionManages the availability, usability, integrity, and security of the data used in an enterprise.Manages all kinds of information in a way that supports an organization's immediate and future regulatory, legal, risk, environmental, and operational requirements. Includes data governance within its scope.
FocusPrimarily concerned with structured data.Concerned with all types of information, structured and unstructured.
Key ComponentsData quality, data integration, data privacy, data strategy, data operations.Information lifecycle management, information security, risk management, legal and regulatory compliance.
How to implement it?1. Establish a data governance council
2. Identify critical data elements
3. Define data quality metrics
4. Create a data dictionary and catalog
5. Implement data stewardship, and
6. develop and implement data policies and procedures.		1. Establish an information governance committee
2. Carry out an information audit
3. Develop an ILM policy 4. Implement information security measures and
5. Create retention and disposal schedules.
When to ConsiderWhen dealing with data quality issues, concerns about data privacy or security, or difficulties integrating data from different systems or departments.When dealing with large amounts of unstructured data, concerns about compliance with legal or regulatory requirements related to information management, or issues with information security or privacy that extend beyond structured data.

Note: While this table aims to summarize the main points, both data and information governance are complex disciplines that involve many interrelated tasks and considerations. It’s essential to understand these in detail to effectively implement them in your organization.

Practical examples of data governance and information governance in action

Here are a few industry-based practical illustrations where you’d find data governance and information governance in action:

Data governance examples

  1. Healthcare institution
  2. Financial services company

1. Healthcare institution

A healthcare institution needs to ensure that patient data is accurate, up-to-date, and only accessible to the right personnel. Data governance in this scenario might involve creating a data dictionary to standardize data entry and implementing data access controls to ensure patient privacy. It would also involve setting up a data stewardship team to continually monitor and improve data quality.

2. Financial services company

A financial services company might implement data governance to manage risk and comply with regulations like the Sarbanes-Oxley Act. This could involve establishing a data governance council to set policies on data usage, data quality, and data privacy, and ensuring that all financial data is audited and traceable.

Information governance examples

  1. Law firm
  2. Manufacturing company

1. Law Firm

A law firm has to manage large amounts of sensitive information, including emails, documents, and court records. Information governance in this case might involve setting up a document management system to store, retrieve, and archive information. It also involves creating a retention schedule to determine when documents can be destroyed and implementing information security measures to protect client confidentiality.

2. Manufacturing company

A manufacturing company might implement information governance to manage its technical specifications, designs, and project documentation. This could involve creating a system to manage and track changes to documents and implementing access controls to protect intellectual property. You would also need to ensure all information is backed up and can be recovered in case of a system failure.

In both of these disciplines, the goal is to manage data and information effectively, securely, and in a way that supports the organization’s objectives. The specific practices and tools used can vary widely depending on your organization’s size, industry, regulatory environment, and specific needs.

Bringing it all together

Data governance and information governance are two distinct but interconnected disciplines that play a crucial role in managing and leveraging organizational data assets. While data governance primarily focuses on establishing processes and policies to ensure the accuracy, availability, and integrity of data, information governance encompasses a broader scope, including data privacy, security, and compliance.

In conclusion, data governance and information governance are both crucial for managing information risks, ensuring compliance, and enabling efficient and effective business operations. While they focus on different aspects of information management, there is a significant overlap, and in most cases, organizations will benefit from implementing both.

Share this article

[Website env: production]