When it comes to data governance and data quality, many companies assume that an all-in-one solution is ideal. After all, having an integrated data quality tool within your data governance platform sounds convenient, right?

In reality, choosing a flexible data governance solution  - One that can connect seamlessly to in-house or best-in-class data quality providers  -  is a much smarter move.

Keep reading to discover the top 5 considerations when integrating a data quality tool with your data governance initiatives.

1. Best-of-breed vs. one-size-fits-all

Improving data quality does not have a one-size-fits-all solution - Different industries, data landscapes, and compliance requirements demand different data quality approaches.

If your company turns to a built-in data quality tool, you can be locked into whatever basic functionality the governance provider offers. This is often limited and not tailored to your specific needs.

However, if your company utilizes a specialized, connected data governance platform, you can choose the best data quality provider that fits your business . This can include a powerful in-house solution or a specialized external provider.

Think of it this way: Would you buy a phone just because it has a built-in camera, even if the camera isn't great? Or would you rather get the best phone and pair it with the best camera when needed? The same logic applies to data governance and data quality.

2. Avoiding vendor lock-in

Choosing a data governance tool with a built-in data quality solution means you're tied to one vendor's ecosystem, for better or worse.

• What if their data quality solution doesn't evolve fast enough?
• What if their pricing suddenly changes?
• What if your business outgrows its capabilities?

With a flexible governance platform, you're in control. You can:

• Integrate with any external data quality tool you choose
• Keep your in-house data quality processes if they work well
• Switch providers whenever you want  without overhauling your entire governance framework

Having flexibility today means future-proofing your teams’ data governance strategy for tomorrow.

3. Scalability & adaptability: Growing on your terms

Your business isn't static - so why should your data governance and data quality tools be? With an open, connectable governance platform, you can:

If your governance and data quality are tightly coupled in a single platform, your teams could lose that agility. A decoupled approach allows your data governance and quality strategies to evolve at their own pace   without unnecessary dependencies.

4. Cost-effectiveness: Pay for what you actually need

A governance tool with an integrated data quality solution might sound like a good deal at first , but are you really getting the best value? You might end up paying for features you don't need. You might have to duplicate efforts if the integrated tool isn't strong enough, leading you to invest in another data quality provider anyway. You might miss out on cost-effective, specialized solutions that would perform better.

With a flexible, connectable governance platform, you can:

• Choose the data quality solution that fits your budget and needs
• Optimize costs by using existing in-house solutions rather than forcing migration
• Scale data quality investments separately from governance, avoiding unnecessary costs

Why overpay for a bundled solution when you can invest in the best tools separately and optimize your budget?

5. Data governance should govern, not do everything

At its core, data governance is about structure, policy, and accountability, not necessarily about handling data quality itself.

Governance platforms should enable organizations to define, enforce, and monitor data policies, but the actual cleansing, validation, and enrichment of data is best handled by dedicated data quality tools.

• A separate data quality solution ensures clean, trustworthy data that governance rules can enforce
• A governance-first approach ensures that policies and standards are correctly applied to that high-quality data.

Governance and data quality should work together ,  but they don't have to be the same tool. By clearly delineating the roles of governance and data quality, organizations can avoid inefficiencies and bottlenecks that arise when governance teams take on too much operational responsibility. 

Instead of being burdened with execution, governance should focus on oversight, ensuring that the right processes, tools, and teams are in place to maintain data integrity. This separation of concerns allows governance to remain strategic, driving compliance and consistency while empowering data teams to leverage specialized tools for quality management.

Stay agile, stay in control

Companies that lock themselves into rigid, all-in-one governance and data quality solutions risk falling behind. By choosing a governance platform that connects to any in-house or external data quality provider, you:

Because at the end of the day, the best data governance solution is the one that gives you the most control, not the one that tries to control everything for you.