Data Governance: Roadmap Considerations for Data Strategy

Your company’s Chief Technology Officer faces the daunting challenge of managing vast amounts of data, often from multiple sources. As data proliferates, so does an organization’s need for a structured, comprehensive approach to its governance. A well-defined data governance roadmap offers a guiding blueprint, providing organizations with a strategic framework to effectively manage, protect, and utilize their data assets. 

Use the links below to jump ahead to relevant sections in this article, including:

Chart depicts the flow of data governance, from regulations to standards to policies to procedures.

The Role of Data Governance in Data Management

Data management and data governance are interconnected concepts that rely on one another for success within an organization's operations. Although the roles and relationships of data governance and data management may change depending on certain contingencies, for the purposes of this article, we will define these processes as follows:

Data Governance Defined

Data Management Defined

“The process of establishing how
data is managed through policies, procedures, roles, etc.”
—The International Information System Security Certification Consortium (ISC)² 


Data management is the practical execution of data governance principles.

It encompasses the day-to-day activities involved in managing data throughout its lifecycle, including data storage, integration, transformation, analysis, and dissemination. Data management ensures that data is organized, accessible, accurate, and reliable, aligning with the governance policies and rules established by data governance. Without effective data management practices, data governance policies would remain mere theoretical concepts, lacking practical implementation and enforcement.

“The formal orchestration of people, processes, and technology to enable an organization to leverage data as an enterprise asset.”
The Master Data Management Institute

“A system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models, which describe who can take what actions with what information, and when, under what circumstances,

using what methods.”
The Data Governance Institute

While data governance sets the guidelines and rules for data handling, data management puts those guidelines into action, ensuring that data is managed effectively, responsibly, and in compliance with the established governance framework.

The Flow of Data Governance

The key elements of a data governance roadmap are regulations, standards, policies, and procedures. These four elements create a flow of governance that organizations utilize to conduct daily operations and remain compliant with data laws. 

  1. When regulations and laws about data capabilities are put into effect, whether locally or federally, companies are required to comply. An example of data regulation is the Health Insurance Portability and Accountability Act (HIPAA). This federal law is the most important regulation of healthcare data in the United States. It directs the adoption of national standards for electronic healthcare transactions while protecting the privacy of individual health information. 
  2. Once regulations/laws are in place, standards, also known as frameworks or best practices, are created by industry professionals to comply with them. For example, the International Organization for Standardization (ISO) develops voluntary international standards in collaboration with its partners in international standardization.
  3. Organizations set out to create policies based on the standards for compliance with regulations. Policies establish the context in which standards are meant to be utilized and provide strategic direction.
  4. From there, procedures are created. Procedures are a group of policies that define explicit, repeatable activities that employees within an organization can follow to accomplish a specific task. 

Components of an Effective Data Governance Strategy

A well-defined data governance strategy establishes clear guidelines, policies, and procedures for data management, addressing key aspects like data quality, privacy, security, accessibility, and lifecycle management. 

A productive data governance strategy must contain these key elements:

  • Data Quality Management. Data governance should encompass mechanisms for monitoring and improving data quality. 
    • Defining Data Quality Requirements
    • Implementing Data Profiling and Cleansing Processes
    • Establishing Data Quality Metrics
    • Continuous Monitoring of Data Quality
  • Data Security and Privacy. A robust data governance strategy incorporates measures to protect sensitive data from unauthorized access, breaches, or misuse. 
    • Implementing Security Controls
    • Utilizing Encryption Techniques 
    • Incorporating Access Management Mechanisms 
    • Privacy Protocols With Relevant Regulations
    • Utilizing Industry Best Practices 
  • Continuous Monitoring and Improvement. Data governance is an ongoing process that requires continuous monitoring, assessment, and improvement. This allows organizations to adapt and enhance their data governance strategy over time.
    • Regular Audits
    • Data Governance Reviews
    • Performance Metrics

The effective implementation of a data governance roadmap relies heavily on the use of advanced technology, which enables organizations to efficiently manage and govern their data assets. Advanced data governance tools and solutions allow organizations to capture, analyze, and visualize data effectively, facilitating informed decision-making and driving business growth.

Tech Solutions To Encourage Data Governance



How It Helps Data Governance


Snowflake is a data warehouse platform built for any cloud-based system.

  • Automates auditing functions
  • Automates validation functions
  • Automates scaling to load, integrate, and analyze data
  • Visualizes data via dashboards


Confluent is a full-scale data streaming platform that helps access, store, and manage data as continuous, real-time streams.

  • Shares real-time data company-wide
  • Encryption techniques ensure data privacy compliance 


Tealium is a customer data platform (CDP) that enables robust customer platforms, personalized experiences, and data-driven insights.

  • Geography-based privacy compliance
  • Standardized data practices
  • Flexible user interface and user experience

Step-By-Step: Create a Successful Data Governance Roadmap

By establishing a data governance roadmap, organizations can align their data efforts with broader business objectives, ensuring that data is treated as a valuable asset that drives decision-making, innovation, and business growth. Creating a successful data governance roadmap requires a number of specific steps.

1. Identify Key Stakeholders and Assets

The first step in creating a successful data governance roadmap is to identify the key stakeholders and assets. This establishes a foundation for effective data governance by fostering collaboration, defining ownership and accountability, and ensuring that the roadmap addresses the company’s specific needs and requirements. It enables organizations to prioritize their efforts, allocate resources effectively, and establish governance structures that support the management and protection of critical data assets. This also ensures individuals or teams are empowered to make decisions and take action regarding data management.

Stakeholders to Identify

Assets to Identify

  • Executives
  • Data Owners
  • Data Stewards
  • IT Personnel
  • End-Users
  • Databases
  • Systems
  • Applications
  • Data Repositories

2. Define Objectives and Scope of Work

A well-defined data governance strategy should clearly outline the objectives and goals it aims to achieve. Clear objectives provide a direction for the data governance efforts within the organization. These objectives can help elevate a data-driven culture.

When defining these objectives and overviewing the scope of work, it's important that all stakeholders are a part of the same conversation. This helps create a shared vision, enhances organizational alignment, and provides a roadmap for success in managing, protecting, and leveraging data effectively.


Objectives to Identify

  • Data Quality
  • Data Privacy
  • Compliance
  • Data Integration

3. Establish Policies and Procedures

Once the information is identified and defined, establishing policies and procedures will follow. These are vital to ensuring consistent and effective data management practices. Organizations with well-defined policies and procedures can maintain data quality and integrity, comply with regulatory requirements, mitigate risks, and establish accountability. Furthermore, they enable effective communication, support decision-making, and provide a framework for adapting to technology—and businesses must change to survive. 

Policies and Procedures to Establish

  • Data Classification Policy
  • Data Access and Authorization Procedure
  • Data Quality Management Policy
  • Data Privacy Policy
  • Data Retention and Archiving Policy
  • Data Security Policy
  • Data Governance Committee Charter
  • Data Incident Response Procedure
  • Data Training and Awareness Program

4. Assign Roles and Responsibilities

Assigned roles and responsibilities promote accountability and clarity. Assigning roles and responsibilities can be done by taking the identified stakeholders and delegating what assets each stakeholder is responsible for. This is completed as the fourth step because roles and responsibilities may change depending on the given context when establishing policies and objectives.

5. Develop a Data Catalog

A data catalog serves as a centralized inventory and reference point for all data assets within an organization. It provides comprehensive metadata about the data, including its source, structure, meaning, and relationships, making it easier to discover and understand the available data. Organizations can improve data visibility, promote data sharing, and enable self-service data access with the help of a data catalog. It facilitates data governance by allowing stakeholders to understand the data's context, lineage, and quality.

When developing a data catalog, a few key items should be included:

  • Graphic Design Style Elements
  • Metadata Standards
  • Lineage
  • Organizational Standards

Data Governance Best Practices

Data governance requires that different operations, teams, and individuals work together. This is a significant challenge for organizations because it only takes one person to start the divide of information. When implementing a data governance roadmap into everyday practices, it’s important to: 

  1. Build a foundation
  2. Create organizational awareness
  3. Encourage engagement, and
  4. Focus on adoption techniques

Leave it to The Experts at Concord

Data governance is a small piece within the larger picture of data management. By implementing a data governance roadmap, your organization can effectively manage and govern its data assets, ensuring accuracy, quality, security, and compliance. To fully optimize your resources and stay ahead of changes and challenges, reach out to a specialty tech consultancy firm that specializes in adopting data governance roadmaps.

Getting Started

Concord USA is a consultancy that combines technology and industry depth with a get-it-done culture to enable resiliency, efficiency, and innovation. Whether you are trying to improve customer satisfaction, data strategies, security, or other technological issues, Concord can help. 

Contact us today to learn more about creating data governance roadmaps, overall data management, our Technology Integration Services, and how we can help your business thrive.

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