IDC® ANALYST REPORT ON SYNTHETIC DATA GENERATION
Unlock the power of synthetic data
Learn from analyst firm IDC about synthetic data generation methods, best practices, strategies, and tools, and how to apply them to various use cases, such as software testing and machine learning model training.
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Learn from the experts how to choose a synthetic data generation tool:
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Combine key generation methods to optimize data accuracy and compliance.
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Ensure your solution covers the entire data journey, from source to target.
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Maintain referential integrity when generating data across multiple systems.
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Support complicated data relationships and hierarchies.
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Empower your team with self-service data generation tools.
Vital Market Research and Analysis
"A comprehensive synthetic data solution should address the entire life cycle from source to target, including data preparation tools to extract and mask the data, and tools that data consumers can use to control data usage and versioning, loading and reserving data, rollback, and other functions. It should also provide capabilities for self-service access by end users, reducing their dependence on data teams.."
