3-step guide to smarter test data management
Curiosity’s 3-step approach to test data management allows you to gain a deep understanding of your...
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In today’s data-driven landscape, the ability to explore and understand your data isn't just a nice-to-have, it's essential. Data discovery enables organisations to understand, organise and uncover hidden patterns, trends, and insights in their data, that drive smarter decisions, enable AI-readiness and improve software delivery.
Dynamic, continuous discovery empowers teams to deliver high-quality, compliant software more efficiently, while reducing costly risks and rework.
Without effective data discovery, gaining a detailed understanding of your data landscape, how it's structured, and how it flows across systems is simply not possible.
When relationships between systems, databases, and business rules aren’t clearly defined or documented, testing teams struggle to generate or subset accurate test data. Limited or no visibility into data and its dependencies means that teams aren’t able to monitor system changes or the impacts on their data and processes, increasing the likelihood of costly failures.
Some common characteristics in enterprises affected by this include:
The absence of a centralised data repository, or clear documentation to detail data structures, relationships and business rules.
Inconsistent practices and teams operating in siloes, each using their own tools and methods.
A tendency to heavily rely on cloning production data for testing, which can introduce security, compliance and quality risks.
When organisations lack effective data discovery practices, the consequences ripple across teams, systems, and business outcomes. Poor visibility into data structures, changes, and relationships leads to inefficiencies, poor testing practices, and increased operational risk.
Here are four common impacts of poor data discovery:
Teams often resort to using outdated or cloned production data that lacks the diversity and accuracy required for robust testing. This exposes organisations to compliance and security risks.
Without a clear understanding of data coverage, critical test scenarios are missed. This leads to undetected issues making it into software releases, damaging user trust and increasing rework.
Manual effort is spent identifying, extracting, or preparing test data, often repeating the same tasks across teams. This slows delivery cycles and impacts the organisations’ ability to move quickly.
Without a standardised, centralised view of data, teams operate in silos with different tools and inconsistent practices. This hinders collaboration and prevents scalable, high-quality delivery.
To address these challenges and unlock the full value of your data, you need more than just access to your data. You need visibility, control, and actionable insight. Here’s what that looks like in practice:
A clear, up-to-date view of all data systems, including underlying structures, sensitive data, such as PII, and the relationships between systems and processes.
A solution that can intelligently scan and map data relationships across your environment, and use that insight to power essential activities like test data generation, masking, and subsetting.
Tools that allow you to track data over time, monitor and be alerted to structure or content changes, and proactively assess how changes might impact downstream systems or processes.
An organised, centralised approach to managing data that ensures accuracy, consistency, and compliance, while supporting agile development and high-quality software delivery.
Curiosity’s centralised, end-to-end Enterprise Test Data platform is designed to give you full control and visibility over your data landscape.
With Enterprise Test Data, you can build:
Gain a deep understanding of your data with advanced profiling tools that automatically discover and map relationships between tables, fields, and systems. Our platform uncovers how your data assets are interconnected, providing a complete picture of how data flows throughout your organisation.
Create a unified, centralised repository for all metadata and business rules, where cross-functional teams can collaborate seamlessly. Curiosity automatically maps and catalogues your data assets, offering a comprehensive glossary view of what data you have and how it’s used, ensuring consistency across departments.
Use the insights you’ve gained into your data landscape to generate high-quality, compliant test data. Detect and classify personally identifiable information (PII) and commercially sensitive data, ensuring your tests remain secure while meeting regulatory requirements, and understand where your most critical data is stored and how it’s being used.
Build a complete picture of your data landscape with data discovery to power data delivery, compliance, and coverage across your whole enterprise. Leverage Curiosity’s co-pilot AI to interact with the platform through a natural language interface. Gain contextual answers and insights into your data to enhance and streamline your data discovery.
Gain a complete understanding of your data and application landscapes with Curiosity's Enterprise Test Data.
Gaining clarity on your data and structures is the first step in your test data journey. Read a resource, or meet with an expert to continue evolving your testing and development practices.
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