SAS tackles data scarcity with novel synthetic data generator that elevates AI across industries

SAS Data Maker a secure, enterprise-grade synthetic data generator that creates statistically representative data without exposing sensitive or regulation-protected information is now available in the Microsoft Marketplace, the unified online destination for customers to buy trusted cloud solutions, AI apps and agents to meet their business needs.

SAS Data Maker, a new offering from global data and AI leader SAS, features open, extensible architecture and enterprise-grade connectors to enable rapid deployment and integration into existing data ecosystems, while combining data augmentation and generation algorithms into one single tool. The solution generates synthetic data that replicates real data’s statistical, relational and temporal characteristics without risking sensitive information, and it supports regulatory readiness with lineage, audit logs and defensible privacy measures.

SAS Data Maker is now available to tackle data scarcity and enhance the speed and quality of AI development.

“Synthetic data that is accurately generated and rigorously validated is an indispensable resource for robust and trustworthy AI models. But accessing large and diverse real-world data can be challenging given increasing privacy concerns, legal restrictions and high data acquisition and annotation costs,” said Kathy Lange, Research Director, AI Software at IDC. “SAS has delivered a solution that not only addresses these challenges but also enhances the speed and quality of AI development.”

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The SAS synthetic data difference

Key differentiators of SAS Data Maker include:

• Enterprise-grade trust and capabilities: Unlike startups or less-seasoned vendors, SAS brings decades of credibility and expertise in regulated industries, including banking, health care and government, that can benefit from synthetic data. SAS Data Maker also provides multi-table source data, time series data and differential privacy to support enterprise-level synthetic data requirements.
• No-code interface: SAS Data Maker offers a user-friendly graphical user interface (GUI) for business users, helping democratize synthetic data and enable broader enterprise operationalization.
• Built-in data quality and evaluation tools: The built-in tools of SAS Data Maker support a variety of generation methods and evaluate the quality of synthetic data using visual metrics, ensuring statistical fidelity to real-world data sets. Many competing products lack robust validation or offer only programmatic access through APIs, without GUI-based quality checks.
• Privacy-enhancing technologies (PETs): With the PET capabilities of SAS Data Maker, users can leverage synthetic data as they would real data without changing existing workflows, seamlessly swapping real/synthetic data in and out of pipelines. Many other PETs require significant workflow changes and significant investments in new tools and processes.

In November of 2024, SAS acquired the principal software assets of Hazy, a pioneer and leader in synthetic data technology. The integration of Hazy technology in SAS Data Maker equips organizations with enhanced synthetic data generation capabilities and offers unparalleled opportunities to harness data safely and effectively, enabling users to experiment and model scenarios that were previously out of reach.

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Accelerating time-to-value for data and AI investments

The general market availability of SAS Data Maker follows a successful private preview period, during which customers across industries – including health care, financial services and government – validated the product’s ability to simulate complex data scenarios, fill gaps in training data and support robust model development. Feedback from these early adopters helped shape the final product, ensuring it meets the real-world needs of data scientists, analysts and developers.

Global industry organizations that previewed SAS Data Maker reported measurable impacts. For example:

• Synthetic data generation closed a data gap for a UK financial services firm to allow training of credit scoring models. The result was a 28% improvement in model accuracy with facilitated machine learning efforts, supporting potential reduction in losses.
• For a US health care provider, SAS Data Maker provided a secure platform for simulating patient behavior and outcomes, testing treatment plans and choosing optimal care paths. The solution reduced risks to customer privacy and enabled patient benefit from data-driven research.
• A European telecom company was able to reduce data access time from weeks to minutes, enabling a more up-to-date customer churn predictive model and helping to improve customer retention.

“Effective, impactful AI needs appropriate and sufficient data – and synthetic data is a game changer for organizations looking to innovate responsibly,” said Brett Wujek, Head of Next-Generation AI Product Strategy at SAS. “SAS Data Maker represents a pivotal step in our commitment to innovation in the next generation of data management and AI and to support industry data needs for trustworthy AI and decision intelligence.”

SAS Data Maker is initially available in the Microsoft Marketplace with plans for additional supported cloud providers and integration into SAS^® Viya^® – a cloud-native, end-to-end data and AI platform for data preparation, model development and deployment.

Also available in the Microsoft Marketplace is SAS Viya Workbench, a cloud-based coding environment purpose-built for developers, data scientists and modelers to experiment and build highly performant models fast with SAS, R or Python through Visual Studio Code, Jupyter Notebook or SAS^® Enterprise Guide^®.

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