EuroSTAR 2026: Quality Engineering Starts with a Strong Foundation

Test Data: The Overlooked Foundation

During conversations about test data, we noticed how many organizations continue to face the same challenges. Teams want to release faster, automate more, and take advantage of AI-driven capabilities, yet they struggle with the availability, quality, and usability of test data.

And despite its importance, test data often receives less attention than it deserves.

During an Accenture session, of Anastasia Simou test data was compared to the “middle child syndrome”: it is always there, but often receives less attention than major initiatives such as AI, automation, and digital transformation.

That comparison felt remarkably accurate.

Everyone wants to accelerate development. Everyone wants more automation and greater use of AI. But without high-quality test data, those ambitions become much harder to achieve.

You can build a beautiful house, but if the foundation is weak, problems will eventually appear.

The same applies to software quality.

AI, Automation and Quality Engineering Depend on Reliable Data

AI can accelerate many aspects of software delivery, but it does not automatically improve the quality of the underlying data.

When test data is incomplete, outdated, inaccessible, or non-representative, teams are forced to rely on workarounds. They test with unrealistic datasets, wait for manual refreshes, depend on full copies of production environments, or avoid critical scenarios because the right data simply is not available.

This limits not only testing effectiveness but also the value AI can deliver.

AI-driven testing relies on representative and trustworthy data. Test automation relies on predictable and repeatable test datasets. Quality engineering relies on a connected ecosystem where people, processes, environments, tooling, and data work together.

That is why test data should not be viewed as an operational concern. It is a strategic enabler of modern software delivery.

Turning Test Data from a Bottleneck into an Accelerator

Many organizations experience test data as a bottleneck.

Obtaining data takes too long. Production data cannot be used due to privacy regulations. Environments are large, expensive, and difficult to refresh. Teams depend on database administrators or centralized specialists to provision the data they need.

A mature test data management approach changes that dynamic.

With secure, realistic, and reusable test datasets, teams can work faster and more independently. Data masking helps protect sensitive information. Synthetic test data generation creates safe and scalable alternatives. Data subsetting reduces infrastructure complexity while maintaining data relevance. And self-service capabilities enable teams to access data when they need it.

Instead of slowing down software delivery, test data becomes a driver of quality, speed, and innovation.

Quality Engineering Requires a Strong Foundation

Quality engineering is about much more than testing at the end of the development lifecycle. It is about building quality into every stage of software delivery.

That requires close collaboration between development, QA, DevOps, security, and data teams.

But collaboration becomes difficult when the foundation is not in place.

If test data is not secure, compliance risks increase.
If test data is not representative, test results become less reliable.
If test data is not readily available, delivery pipelines slow down.
If test data cannot be automated, CI/CD processes remain dependent on manual effort.

Organizations can certainly make progress without addressing these fundamentals. New tools can be introduced. Processes can be improved. AI initiatives can be launched.

However, sooner or later, the same limitations resurface if the foundation remains weak.

In many ways, it is like building upward without strengthening the structure underneath.

The Power of the Community

Beyond the technology discussions, one of the most valuable aspects of EuroSTAR was reconnecting with people across the community.

We met customers, partners, industry experts, and fellow practitioners from multiple countries. Each organization faces different challenges, but they share a common goal: delivering software that is better, faster, and more reliable.

That is what continues to make EuroSTAR such a valuable event.

Not only because of the sessions themselves, but because of the conversations in between. Those discussions often reveal what organizations are truly struggling with, where innovation is creating value, and where practical realities are still catching up with technological promises.

Looking Ahead

After a productive week in Oslo, we return with fresh ideas, valuable conversations, and renewed energy to help organizations advance their quality engineering journey.

From AI and test automation to new tools, skills, and delivery practices, the industry continues to evolve rapidly.

But one message remains constant:

Start with the foundation.

Because a strong foundation makes every next step possible.