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Features

DATAMIMIC features

DATAMIMIC offers a comprehensive set of features to streamline your model-based test data generation process:

Model-Driven Approach

DATAMIMIC embraces a model-driven approach that offers significant benefits in terms of easy maintenance and abstract test data processing:

  1. Simplified Maintenance: With DATAMIMIC's model-driven methodology, maintaining test data becomes straightforward. Users define data models that serve as blueprints for data generation. When changes are required, they can be implemented at the model level. This ensures that modifications are centralized and don't entail extensive rework throughout the testing process. It's as simple as adjusting the model to reflect updated requirements.

  2. Abstract Data Processing: The model-driven approach abstracts the complexities of test data processing. Users work with high-level data models rather than delving into intricate data structures. This abstraction shields testers and developers from the nitty-gritty details of data generation, making it easier to focus on the functional aspects of testing.

  3. Efficient Adaptability: As project requirements evolve, DATAMIMIC's model-driven approach provides an efficient way to adapt. Whether it's accommodating changes in data formats, adding new data sources, or modifying data relationships, adjustments can be made within the model, ensuring adaptability without disruptions.

  4. Consistency and Reliability: Abstract test data processing through models promotes consistency and reliability. Data generation adheres to predefined rules and constraints, reducing the likelihood of errors and ensuring that test scenarios remain faithful to the intended data structure.

DATAMIMIC's model-driven approach empowers teams to manage and process test data at an abstract level, streamlining maintenance and enhancing adaptability. By abstracting the intricacies of data processing, it fosters efficiency and reliability in the testing process.

Abstract Data Transformation

  • DATAMIMIC transforms various inputs into flexible entities for diverse outputs like SQL, XML, JSON, CSV, and more.

Advanced JSON and XML Handling

DATAMIMIC offers expert handling of complex data structures in both JSON and XML formats. It provides the ability to work with intricate and deeply nested JSON and XML data, allowing you to create, manipulate, and generate structures with infinite levels of nesting.

  1. Nested Structure Generation: DATAMIMIC allows you to effortlessly create JSON and XML objects with nested structures. You can define objects or elements containing other objects/elements, arrays, and various data types within a single structure.

  2. Hierarchical Data Modeling: The tool supports hierarchical data modeling, enabling you to represent complex relationships between data entities within your JSON and XML structures. This is particularly useful for modeling NoSQL databases, XML schemas, or other complex data models.

  3. Deeply Nested Objects/Elements: DATAMIMIC supports the creation of deeply nested JSON objects and XML elements, allowing you to mimic real-world data scenarios where data can be highly interconnected and hierarchical.

  4. Flexibility and Customization: You have the flexibility to customize every aspect of your JSON and XML data, from defining complex data structures to specifying how data is generated and formatted within the objects or elements.

Data Anonymization and Pseudonymization

  • Effortlessly configure field-level obfuscation ensuring ease of maintenance and adaptability.

GDPR Compliance

  • In-built features ensuring data privacy and protection.

AI-Enhanced Data Generation

  • Advanced algorithms and data analysis features to create realistic and diverse data sets.

High Performance

  • Optimized for handling large data volumes efficiently. DATAMIMIC is e.g. used to process and obfuscate millions of payment transactions in real time.

Intuitive User Experience

  • User-friendly interface and clear documentation.

Flexible and Scalable

  • Suitable for various project sizes and complexities.

Extensive Function Library

  • Wide range of in-built generators and functions for realistic data creation. These functions can be freely extended with your custom code.

Seamless Integration

  • Easy integration with existing development, testing environments, and CI/CD.

Automatic PII Detection and Masking

When generating a DATAMIMIC model from database metadata, the platform automatically detects fields that are likely to contain Personally Identifiable Information (PII). These fields are replaced with the special marker #SENSITIVE in the generated model. This ensures that sensitive data is masked by default, helping you comply with data privacy regulations and best practices. You can review and adjust these fields as needed before generating or exporting your synthetic data.