Data governance vs. Data management: Main differences

Data governance vs. Data management: The blueprint and the contractors

The most popular analogy to make the distinction between data governance and data management is borrowed from construction.

Data governance is the blueprint. It specifies standards for construction, how big certain rooms should be and specific functions for certain rooms (for instance, the kitchen versus the garage). The blueprint also specifies building standards to make sure that the completed structure is built to code.

Conversely, data management represents the primary contractor and subcontractors who actually engage in the work of constructing the building. While they refer to the blueprint to make sure that they’re adhering to its requirements, they also get into the low-level details of construction that the blueprint doesn’t address.

Can you build a building without a blueprint?

Technically, yes, but construction efforts will likely be much less efficient and effective, and the final product is much more likely to have problems down the line. Similarly, without a solid contractor, a blueprint is just a set of documentation. Data governance and data management need one another.

Without data governance in place, data management stands the risk of burning through limited IT funds to develop a set of data systems that are inadequate for the organization’s needs, or that run afoul of domestic and international privacy regulations. And without a robust data management structure in place, data governance is simply a set of rules and specifications that don’t get implemented.

What is the role of data governance in organizations?

Data governance sets forth the rules, standards, and procedures for data access, use, and management. It is the practice of managing how the data that is being managed is processed through the organization. In particular, it defines the ownership, stewardship and operational structures needed to ensure that you’re managing corporate data as a critical asset.

At its heart, data governance is strategic: it defines data-related goals and objectives that in turn produce a set of principles, standards, and practices. These are applied to the end-to-end lifecycle of data (collection, storage, use, protection, archiving, and deletion) to ensure your data is reliable and consistent. Data governance:

• Establishes organizational structures
• Confirms who owns which data within the organization
• Records business terms and metrics
• Specifies document processing
• Enforces rules and policies

One of the overarching goals of data governance is to create harmony between data across various business units. Another goal is to ensure data is used properly across your organization, which can be mission-critical depending on the regulations governing that organization’s industry.

It's also important to acknowledge that data governance isn’t strictly the purview of IT: it’s an organizational imperative that ensures data is treated with appropriate importance, security, and compliance, regardless of the form it takes.

Components for successful data governance

Data governance impacts portions of the business well outside of IT, so it’s critical to have the right non-IT people at the table, including but not limited to the following:

• Subject matter experts (SMEs), who can help determine the standardized terms for the organization, as well as data quality thresholds for your business processes.
• Legal and security specialists, who can help ensure data privacy and protection.
• Data stewards, who are responsible for ensuring data quality.
• Cross-functional leadership, who can help resolve disagreements between different functions of the organization.

With your governance board in place, you will need to incorporate the right principles so that the board has guidance in making decisions, including:

• Data quality—The overall approach needs to ensure that the data is kept as accurate, reliable, and actionable as possible.
• Data access—The system offers a streamlined process for access requests and approval procedures. The objective is to make data readily available to all who need access to it.
• Data privacy—Safeguard the data and personal information of clients, employees, and stakeholders.
• Data protection—Protect the organization’s data from potential threats and malicious actors by using security measures to protect vital assets.
• Regulatory compliance—Ensure that the organization’s data handling methods meet legal or jurisdictional requirements.

How is data governance different from data management?

To better understand the strategic versus tactical nature of data governance versus data strategy, a direct comparison can be helpful.

Data governance activities

What does data governance look like?

At their core, data governance activities fall into one of three broad categories:

Evaluate

The data governance body needs to assess internal and external operations to make informed decisions about how data will be used and controlled. Key focus areas include internal business operations, consumer behavior, market trends, and the evolving regulatory environment.

Direct

The data governance body communicates direction to internal (management and staff) and external (partners and suppliers) stakeholders regarding its approach to the use and control of data, and particularly how it intends to leverage data for business advantage while complying with regulatory requirements.

It's worth emphasizing that the data governance body is communicating direction, not a mandate. That direction may be communicated via:

• Vision and mission
• Ethics and principles
• Strategy, policy, and controls
• Goals and objectives

Monitor

Once the data governance body has determined its chosen direction and communicated that direction to the organization, it will need to check regularly to make sure that a) its chosen direction is being followed, and b) that the direction remains relevant to the organization’s needs. This generally means reviewing information and reports received from the management team.

However, monitoring can’t and shouldn’t be conducted in a vacuum. Independent auditors and third-party evaluators—including regulators—should have some level of involvement in ongoing monitoring activities.

Data governance and data management challenges

As companies have become more aggressive in utilizing their data, concerns over privacy have grown. In response, several regulatory bodies have responded in recent years with regulations that directly affect what a business may do with its data and how it must handle it.

• The Health Insurance Portability and Accountability Act (HIPAA) in the US dictates how data related to healthcare must be managed and how it may be used.
• The GDPR is the first regulation of its kind specifically mandating how online data may be gathered, and what companies may utilize it.
• Passed in 2018, the CCPA was the first US response to the GDPR. Four other states followed suit in 2023, with others expected to implement their own privacy laws in coming years.

As this regulatory environment becomes increasingly complex, businesses will have to balance compliance requirements alongside the ongoing challenge of managing and governing their large and ever-growing data repositories in a way that will give them a competitive advantage in their business operations.

Additional resources