Why every organisation needs data discovery
Dynamic, continuous discovery empowers teams to deliver high-quality, compliant software more...
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Growing enterprise complexity, compliance and regulatory changes, and advancements in AI are all critical factors of the modern test data landscape. For organisations to keep up with the pace of change, they must be equipped with test data management solutions that can overcome these new challenges.
Organisations are reaching hundreds to thousands of applications and systems (legacy, ERP, SaaS, NoSQL), creating silos and making it harder to monitor and govern their application landscape.
Teams are stuck firefighting, lacking the time and tools to deliver high-value solutions and the ability to proactively plan for future project or data needs.
Enterprises manage billions of rows of data, overwhelming traditional test data practices, that cannot support or process within a reasonable time frame.
Regulations like GDPR and the AI Act require stringent governance, and without robust, automated compliance practices in place, organisations may fall behind, increasing their risk of breaches.
Enterprises must deliver higher ROI with leaner teams and budgets. Without successful AI adoption, inefficiencies persist, delaying test data workflows and increasing costs.
AI initiatives demand clean, unified and compliant data streams, but enterprises struggle with preparation and integration across multiple systems and formats.
In a fast-paced, AI-driven software world, efficient, compliant, and unified test data is no longer optional.
Robust, agile and automated processes are now a necessity in modern test data environments, for enterprises to keep pace with competitors, meet regulatory standards, and protect their reputation.
The teams feeling this most are test data, compliance and AI. They are usually solving the same data problem three times over, each with their own tools and their own version of the truth.
Three teams depend on the same data. Curiosity gives each of them what they need without building three separate versions of the truth.
Give development and testing accurate, high quality data quickly. Find, make, mask, subset and clone the right data from one platform, with every dataset linked to the requirements and tests it supports.
Know what your data contains, how sensitive it is and where it flows. Continuous monitoring and an enterprise dictionary of every data structure give you a trusted view you can put in front of an auditor.
Bring AI into the development chain with control, and train it on data you completely understand. High quality, compliant training data comes from the same layer your teams already trust.
Data provisioning in most enterprises is fragmented and slow. Teams move between separate tools to find, allocate, make, mask, clone and create data, then wait for a full refresh that overwrites the test data they had carefully built.
Curiosity replaces that with one platform. Teams ask for exactly the data they need and receive a small, accurate, compliant set on demand, built through subsetting, masking and synthetic generation working together across every system at once.
Because data is linked to your requirements and tests, you can see which data each test needs and what breaks when a requirement changes. The problem was never the test tool, it was the data.
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Knowing where your databases are is not the same as knowing what is inside them. Sensitive data hides in free text fields, in badly named columns and in copies nobody remembers making.
Curiosity scans the actual content of your data, not just the column names, and keeps scanning as it changes. The result is an enterprise dictionary of every data structure: a trusted view of what your data means, how sensitive it is and where it flows between systems.
That understanding is what turns compliance from a claim into something you can prove. Masking is applied consistently across every system and environment, so relationships hold, integration tests keep working and the evidence is ready when an auditor asks.
AI is arriving in two places at once. It is speeding up the development chain, from requirements through to tests and data, and it is being trained on enterprise data to power new products and decisions.
Both depend on data you can trust. Curiosity uses AI to accelerate requirements, test generation and data delivery while keeping the output controlled, repeatable and traceable back to a model your teams have agreed on.
For training, the rule is simple: only give an AI data you completely understand. Curiosity delivers high quality, compliant training data, whether masked, subsetted or fully synthetic, from the same data layer your testing and compliance teams already rely on.
At Curiosity, our AI-driven test data platform has set the global standard for test data management. Our AI-powered approach is built to simplify complexity, enable seamless operations, mitigate risks, and prepare your data for AI adoption.
Uncover smarter test data, with Curiosity’s all-in-one, AI-accelerated platform. Offering integrated, secure, and intuitive tools to simplify complex application landscapes and overcome test data management challenges.
Build a complete picture of your application landscape, bringing thousands of data sources into a single view, fostering effective test data management strategies.
Take advantage of advanced masking and data generation capabilities to deliver compliant and secure data to your teams, whenever and wherever they need it.
Seamlessly join together diverse, compliant data, and gain clarity on your data structures, to help your organisation confidently adopt AI.
Move from reactive slow test data delivery, to advanced, AI-powered insights, actions, and delivery. Test data has never been easier.
Read a resource, or speak with an expert, to discover how you can transform your enterprise test data management.
Dynamic, continuous discovery empowers teams to deliver high-quality, compliant software more...
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