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Common Data Governance Mistakes and How to Avoid Them

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Brian DeLuca is a co-founder and CEO of The Reporting Hub. As a seasoned expert in data, analytics, and business intelligence, Brian brings over 20 years of experience driving innovation and organizat...

5 Minutes

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Data is a critical asset, but its value depends on trust.

For larger teams, missing guardrails can lead to duplicated reports, access chaos, and wasted time verifying numbers. Smaller teams may face different risks, like ad-hoc spreadsheet overrides. It’s not just about locking down access. Good Power BI governance means knowing who can see what, where your data comes from, and whether it can be trusted.

In Power BI, that means setting clear rules from access control to data quality standards. But governance isn’t just about tools. It’s about people, processes, and how your team works with data every day.

Get it right, and you protect your data, stay compliant, and build trust across the business. Get it wrong, and you end up with chaos – conflicting reports, security risks, and wasted time.

In this post, we’ll break down the most common data governance mistakes and how to avoid them. Use these data governance best practices to keep your Power BI setup clean, secure, and built to scale.

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Mistake #1: Treating Governance as a One-Time Project

Many teams assume governance is something you set once and forget. But both your organization and your data are always changing, so your governance must evolve too.

Power BI’s self-service features empower users, but they require intentional governance, like training on dataset creation and naming conventions to prevent fragmentation.

Users need guidance and support to use the tool productively and securely. And IT needs to know reports are optimized and costs are under control.

How to avoid it:

Many teams assume governance is something you set once and forget. But both your organization and your data are always changing, so your governance must evolve too.

Mistake #2: Lack of Ownership or Clear Roles

One of the most common roadblocks in data governance is not knowing who’s responsible for what. When roles aren’t defined, accountability falls through the cracks, and problems like poor data quality, access issues, or report sprawl are harder to manage.

Power BI environments thrive when responsibilities are clearly assigned. Data stewards, report owners, and access administrators each play a crucial role in maintaining organization, security, and scalability.

Data stewards (verify datasets, document lineage)

Report owners (maintain dashboards, retire unused content)

Access admins (manage permissions, audit logs)

For example, a data steward might handle daily data hygiene, while a report owner ensures that dashboards are accurate and compliant. In smaller teams, one person may wear multiple hats.

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How to avoid it:

Set up a simple governance structure from the start. Define who approves access, who reviews report accuracy, and who monitors usage. Even a basic role matrix can go a long way. Clear expectations make collaboration easier and your data more trustworthy.

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Mistake #3: Inconsistent Access Controls

Too much access puts sensitive data at risk. Too little access leads to bottlenecks and frustrated users. Striking the right balance is one of the most common challenges in Power BI governance.

Many teams overlook how Power BI handles permissions. By default, users with Contributor, Member, or Admin roles can access everything in a workspace, including datasets and reports.

RLS filters apply to all roles when defined in Power BI Desktop. However, workspace roles (Admin/Member/Contributor) override RLS in the Power BI Service unless explicitly restricted.

That means if you’re not managing workspace roles carefully, RLS may not function as you expect it to.

Best practice:

Use Power BI’s role-based access controls and assign the right level of permissions for each user. Define roles in Power BI Desktop and apply RLS filters to protect sensitive data. When publishing to the service, double-check who has access and what role they’ve been assigned. Use environments to separate development, testing, and production, and make security part of your deployment process, not an afterthought.

If you’re sharing dashboards at scale, especially with external users, consider an embedded or white-label solution. Platforms like the Reporting Hub enable you to control exactly what each user sees, without exposing your entire Power BI environment. It’s a cleaner, more secure way to manage access while delivering a seamless experience.

Mistake #4: No Single Source of Truth

When teams pull data from different sources or datasets, reports don’t match. This causes confusion and erodes trust in the numbers. Without a single source of truth, decision-making suffers.

Best practice:

Centralize core datasets (e.g., financials, customer records) but allow controlled decentralization for team-specific metrics. Use certified datasets in Power BI to mark trusted sources.

Utilize tools such as Power BI dataflows or OneLake to create a curated and consistent dataset. By exposing only cleansed and standardized data to report creators, you reduce the risk of errors and limit access to sensitive raw sources.

Centralizing data also improves security and performance. Instead of multiple users querying raw databases, dataflows handle extraction and transformation efficiently, especially at scale when delivered through Power BI Embedded. This approach ensures your data remains reliable and your reports consistent, allowing teams to make informed decisions with confidence.

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Mistake #5: Ignoring Embedded Analytics Governance

Embedded BI runs directly within the apps your teams already use. This makes it easier for users to access and understand data lineage, permissions, and governance policies without switching platforms.

Embedded analytics introduces unique governance challenges:

External users may require more stringent access logs.

White-labeling requires hiding Power BI metadata.

API calls must be throttled to prevent misuse.

Tools like Reporting Hub address these by extending Power BI’s native controls.

Best practice:

The best approach is to enforce the same access controls, versioning, and audit standards for embedded solutions as you do for internal reports. This keeps data clean, secure, and easy to work with across all departments.

Reporting Hub is designed to support this by helping teams scale embedded Power BI while maintaining strong governance,so your data stays trusted wherever it’s accessed.

Mistake #6: Not Training or Supporting End Users

Even with well-governed data, users won’t get the full value unless they know how to utilize it. Without clear training and support, people may misinterpret reports or lose trust in the data.

Focus training on:

Metric definitions (e.g., ‘What counts as an active user?’)

Common pitfalls (e.g., misapplying filters)

Self-service boundaries (e.g., ‘When to request a new dataset’)

Best practice:

Provide ongoing training, easy-to-follow documentation, and consistent reporting formats. This helps everyone understand the data’s purpose and how to work with it confidently.

Keeping users informed about governance policies and Power BI updates builds a stronger data culture. Leveraging resources like Microsoft’s official guides, tutorials, and community forums can make training easier and more effective. Consider formal training programs focused on data governance to empower your team and ensure your governance efforts are effective.

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How Reporting Hub Supports Data Governance Best Practices

Reporting Hub is a white-label platform designed to enforce governance at scale. It lets you deliver Power BI content securely, with role-based access and centralized management all in one place.

Reporting Hub extends Power BI governance with:

Automated RLS sync from your identity provider (e.g., Azure AD)

Custom branding to hide Power BI metadata from external users

Usage analytics to track embedded report access

The platform supports secure sharing through custom-branded portals, so you control who sees what, without worrying about per-user costs. Its plug-and-play setup grows with your team or client base, adapting as your data needs evolve.

By transforming Power BI reports into a scalable SaaS offering, Reporting Hub enables organizations to maintain strong governance while sharing insights broadly and securely.

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