What is SAS Data Maker?
SAS Data Maker is a low-code/no-code tool for generating high-quality synthetic data that mirrors real-world data sets. It lets you augment existing data or create entirely new data sets, reducing the cost of data acquisition, protecting sensitive information and accelerating AI and analytics development.
How SAS Data Maker works
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Innovate faster
Get trusted algorithms for data augmentation and data generation in one powerful tool to drive model performance and smarter insights.
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Ensure scalable outcomes
Reduce expenses related to data acquisition and processing time with an alternative to manually collecting real-world data or purchasing third-party data sets.
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Protect your customers
Generate synthetic data that mirrors real-world data and better protects sensitive information. Address data bias challenges by using diverse data collection methods.
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Generate data you can trust
Evaluate data quality with visual statistical evaluation metrics fully automated for auditing the quality and privacy of generated data.
How is synthetic data used across industries?
Data accessibility
Challenge:
Privacy laws limit access to sensitive data, hindering model training and testing.
How synthetic data helps:
Recreates real-world data without revealing private information.
Results:
Speeds model development, reduces compliance risk and enables secure collaboration.
Imbalanced data
Challenge:
Imbalanced data sets skew machine learning models, causing bias and unreliable predictions.
How synthetic data helps:
Generates diverse samples to balance classes and improve fairness.
Results:
Delivers fairer models, stronger decisions and lower data collection costs.
Rare events
Challenge:
Limited data on rare events like climate disasters or equipment failures reduces prediction accuracy and risk preparedness.
How synthetic data helps:
Creates realistic rare-event data for better training and compliance.
Results:
Improves prediction reliability and risk mitigation while cutting data costs.
Insufficient data
Challenge:
Sparse real-world data slows AI development and weakens model accuracy.
How synthetic data helps:
Produces rich, diverse data sets that mirror real conditions.
Results:
Speeds AI delivery, boosts accuracy and drives faster innovation.
Fraud detection & prevention
Challenge:
Limited fraud data and privacy barriers slow model training and accuracy.
How synthetic data helps:
Simulates realistic, private fraud scenarios for safe model training.
Results:
Improves fraud detection, speeds claims and strengthens fraud resilience.
Accelerating drug discovery & clinical trials
Challenge:
Privacy rules and limited patient data slow research and increase bias.
How synthetic data helps:
Generates realistic, privacy-safe patient data sets for broader collaboration.
Results:
Accelerates drug discovery, improves trials and ensures compliance.
Policy development & social program optimization
Challenge:
Agencies lack shareable citizen data, limiting policy analysis and improvement.
How synthetic data helps:
Builds privacy-safe population data for secure sharing and simulation.
Results:
Improves policy outcomes, efficiency and interagency collaboration.
Predictive maintenance
Challenge:
Missing failure data weakens predictive maintenance models.
How synthetic data helps:
Generates realistic failure and operational scenarios.
Results:
Cuts downtime, lowers costs and boosts equipment reliability.
Sales, pricing & promotion optimization
Challenge:
Fragmented sales data obscures trends and weakens demand forecasts.
How synthetic data helps:
Unifies and enhances legacy data to reveal clear patterns.
Results:
Improves forecasting, pricing and profit through data-driven insights.
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SAS Data Maker frequently asked questions
What is SAS Data Maker?
SAS Data Maker is a low-code/no-code tool that generates high-quality synthetic data mirroring real-world data sets. It helps organizations accelerate model development, protect privacy and reduce data acquisition costs by creating data that’s safe to share and ideal for analytics, testing and AI innovation.
What is synthetic data?
Synthetic data is artificially generated information that replicates the patterns and relationships of real data without using actual personal or sensitive details. It enables organizations to analyze, model and collaborate securely – especially in industries restricted by data privacy laws or limited data availability.
How does SAS Data Maker generate synthetic data?
SAS Data Maker uses trusted SAS algorithms to create synthetic data sets from existing data or user-defined parameters. It measures data quality, realism and privacy to ensure that generated data behaves like real data while protecting sensitive information, supporting analytics, model testing and AI development.
How does SAS Data Maker help with limited data access or privacy restrictions?
When strict privacy laws limit data sharing, SAS Data Maker replicates real-world data patterns without exposing confidential information. This enables secure collaboration, innovation and model training across teams while maintaining full compliance with privacy and security requirements.
How does synthetic data improve model fairness and accuracy?
Imbalanced data sets can cause bias in AI models. SAS Data Maker generates realistic examples for underrepresented classes to balance data distributions, improving model fairness, predictive accuracy and decision reliability – without the need for costly additional data collection.
What industries use SAS Data Maker?
SAS Data Maker is used across financial services, health care and life sciences, the public sector, manufacturing and retail. It helps these industries securely generate, share and analyze data for applications ranging from fraud detection to policy development and predictive maintenance.
Is SAS Data Maker secure and compliant with privacy laws?
Yes. SAS Data Maker produces synthetic data that mirrors the characteristics of original data sets without revealing real records. This privacy-first approach supports compliance with data-protection regulations such as GDPR, HIPAA and other global privacy standards.
What are the main benefits of SAS Data Maker?
SAS Data Maker helps organizations:
- Accelerate AI and model development.
- Reduce data acquisition and compliance costs.
- Improve model fairness and accuracy.
- Maintain data privacy and regulatory compliance.
- Enable secure data sharing and collaboration.