The Difference Between Information Governance and Data Governance

Recently, I was in a meeting with stakeholders at a corporation exploring a new information governance program. Midway through the discussion, an IT vice president commented that the effort seemed duplicative of the company’s existing data governance initiative. It was a fair question—but also a revealing one. While the organization’s information governance capabilities were still maturing and clearly in need of strengthening, the proposed activities were entirely distinct from those handled by the data governance team.

Unpacking the Confusion

This kind of confusion is common. The terms “information governance” and “data governance” are often used interchangeably, and not always accurately. Sometimes, it’s a simple naming issue: what one group calls “data governance,” another calls “RIM,” “document retention,” or “information management.” But this isn’t always just semantics. Misunderstanding the roles of these two disciplines can lead to serious misalignment, inefficiencies, and even compliance risks.

Let’s start with the basics. Information governance is a broad discipline focused on managing information throughout its lifecycle. It encompasses records management, privacy, litigation readiness, and access controls. Done well, it enhances compliance, reduces risk, cuts costs and, perhaps most importantly, boosts individual employee productivity and collaboration across departments. Information governance workstreams typically deal with unstructured and semi-structured content like files and emails, which account for the vast majority of a company’s information footprint.

Data governance, in contrast, is traditionally concerned with structured information: data stored in databases and data warehouses. Its focus is on ensuring data quality, accuracy, consistency, and usability. It underpins initiatives like master data management and is central to how companies analyze trends, price products, or identify market opportunities. Where information governance is often compliance-driven, data governance is analytics- and business intelligence-driven.

The Cost of Misalignment

The two camps don’t always agree on hierarchy. At information governance conferences, I often hear that data governance is a subset of information governance. At data governance events, the inverse is argued with equal conviction. But when these debates flare up inside organizations, they’re often less about taxonomy and more about territoriality—who owns what and whose program gets funding.

I’ve witnessed this tension firsthand. At one company, the IT-led data governance group was building a “single source of truth” analytics platform, ingesting data from across the enterprise. Simultaneously, the records management team, as part of its information governance mandate, was aggressively purging ROT (redundant, outdated, or trivial content) from file shares and inboxes. Neither group knew what the other was doing. The data team was frustrated to discover that some historical data they wanted for trend analysis had been deleted. Meanwhile, compliance leaders were alarmed to find that sensitive customer information had been ingested into the data lake with no retention policies or privacy controls in place. It was a textbook case of siloed good intentions leading to counterproductive outcomes.

Bridging the Divide

These conflicts are both avoidable and unnecessary. The reality is this: information governance and data governance are separate but complementary disciplines. The key is to leverage the strengths of each to support the other.

Information governance programs excel at classification, privacy enforcement, and lifecycle management. These are critical tools for keeping data lakes and analytics platforms secure and compliant. For example, tagging documents that contain personal or regulated data as part of an information governance initiative makes it easier for data governance teams to determine what should or shouldn’t be ingested into an analytics environment.

In turn, data governance efforts often yield standardized definitions and data inventories that are invaluable to information governance. If the data governance team defines what a “customer” is across systems, the information governance team can use that definition to ensure consistent retention, access, and compliance handling of all customer-related information, whether it's in a contract, an email, or a CRM system.

In short, each side feeds the other with intelligence, standards, and policy direction. When coordinated, both programs are stronger.

Striking a Balance

Ultimately, governance is about balance. Organizations can’t afford unregulated information sprawl, where anything goes and compliance is an afterthought. But they also can’t afford overly restrictive practices that hinder innovation and insight. An executive might ask, “Do we really need both programs?” The answer is unequivocally yes.

Strong information governance without data governance may keep you compliant but leave you unable to fully capitalize on your data. Robust data governance without information governance might deliver impressive analytics while simultaneously exposing you to legal, regulatory, or reputational risks. Only when both disciplines are present and aligned can an organization truly manage information as both a strategic asset and a liability.

I really don’t care what the program is called. What I do care about is that in today’s environment of exploding data volumes and rising regulatory scrutiny, getting alignment isn’t optional; it’s essential.