3 steps to improve Test Data Management. Download Gartner's report.
Automation has become the big bet for QA teams. Yet in many organisations, the expected growth never materialises.
In 2025, we analysed the reality of more than 150 companies across Europe and Latin America to understand what is holding that evolution back. The conclusion was clear: automation is a priority, but it does not scale.
Over 66% of teams say expanding automation is their main objective. However, more than 50% do not exceed 40% automated coverage, and 34% identify the lack of suitable test data as the primary obstacle.
The pattern repeats itself. When test data is not managed as a strategic asset—consistent, secure, and available on demand—automation loses stability, cycles slow down, and risk increases.
Most improvement initiatives focus on frameworks, tools, or pipelines. Organisations invest in automation expecting a rapid leap in efficiency.
Yet the study points to a different reality: 32.7% of teams say test data management consumes a significant share of their effort, and 22% still create test data manually.
The symptoms are clear:
The result is reactive testing that is difficult to scale.
Scaling QA doesn’t require more automation scripts; it requires changing how we think about data.
Test data managed as an asset is not simply data that is available—it is an all-powerful dataset:
This means moving from a craft approach to an industrial one.
The approach proposed by icaria TDM is not about adding more manual processes. It is about structuring test data management as a complete system: coordinated mechanisms, metrics, and traceability.
The journey towards that maturity is built in layers.
In complex environments, the first blocker is often regulatory. Under pressure to test with realistic data, many organisations resort to large-scale production copies. The problem is that this shortcut creates risk and slows progress.
Embedding data masking into the flow with icaria TDM changes the conversation. Automated discovery of sensitive data, dissociation policies, and multi-technology execution turn privacy into a structural capability.
The question stops being, “Can we use this data for our tests?” and becomes, “How do we design it so it’s useful and safe?” That unlocks the next layer.
Once risk is addressed, the next challenge emerges: scale.
Cloning entire databases is not the same as realism; it is cost and inefficiency.
Intelligent subsetting makes it possible to define complete functional domains—for example, a customer and all their relationships across different systems—and extract only what is needed while maintaining referential integrity.
The impact is immediate:
Here, data stops being a copy and becomes a controlled construct.
In the previous layer, data still depends on complex queries maintained by specific individuals. The organisation does not have a system; it has internal dependencies.
Introducing data archetypes makes it possible to define, consistently, what each business term means from a shared perspective of business and testing. icaria TDM allows these archetypes to be defined and enables teams to find suitable data instances for each test. The associated search tool turns discovery into a standardised, reusable, and traceable process.
Knowledge stops being owned by a few and becomes shared. And with that, data begins to behave as an organisational asset rather than an individual one.
The real step change happens when data is integrated into the pipeline.
Requesting a dataset on demand, injecting it automatically before the test run, and validating the outcome from a data perspective removes the most common bottleneck in continuous testing. Automation is no longer limited by data availability—data moves at the same pace as code.
In mature organisations, data is not hunted down before execution; it is designed as part of the test case.
Each test includes the conditions its dataset must meet. The system finds or generates it, protects it, delivers it, and restores it whenever needed for reuse.
At this layer, rework is reduced, instability is eliminated, and every test becomes independent—the point at which data definitively becomes a strategic asset.
When test data management reaches a structured model, the impact stops being purely technical and becomes financial and strategic.
With icaria TDM, test data stops depending on manual processes and becomes a measurable, repeatable organisational capability. This translates into tangible benefits:
When data stops being an operational problem, the benefits start to show across the organisation.
In projects where icaria TDM has been implemented, organisations have observed measurable outcomes such as:
These results do not come simply from adopting a tool, but from adopting a structured model where test data is managed as a product, with on-demand provisioning, traceability, and integrated compliance.
icaria TDM enables that shift: a coordinated system in which data is consistent, secure, repeatable, and available exactly when needed.
In complex environments, scaling QA is not only about automating more—it is about turning test data into critical infrastructure that accelerates delivery, reduces risk, and creates competitive advantage.
Talk to our team and discover how icaria TDM can completely transform your organisation’s efficiency in using test data.
