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AI-Driven Data Simulation for Testing and Compliance
The Synthetic Data Generator provides realistic, anonymized datasets to support testing, analytics, and compliance initiatives.
Key Features
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Secure Data Masking: Protects sensitive information while maintaining realistic patterns.
- Customizable Data Sets: Generates domain-specific datasets for training models and testing applications.
- Regulatory Compliance: Ensures adherence to GDPR, HIPAA, and other data privacy regulations.
- Scalability: Generates large-scale datasets for AI model training and performance benchmarking.
Benefits
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Enhances machine learning and AI model training with realistic data.
- Protects sensitive customer data during testing.
- Reduces reliance on production data for testing, ensuring compliance.
- Accelerates product testing cycles with readily available synthetic datasets.
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Sample Use Case 1: Application Testing Use Case
Scenario: Generating Test Data for Software Development
Business Challenge:
A global banking institution developing a new online banking application faced challenges in acquiring real customer data for testing due to security and privacy concerns.
Solution with PDI Synthetic Data Generator:
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Creates realistic customer transaction data without exposing sensitive information.
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Maintains database schema and relationships, ensuring the test environment mirrors production.
- Generates edge-case scenarios, helping developers test different transaction conditions.
Benefits:
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Speeds up application testing by eliminating dependencies on real user data.
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Enhances security by avoiding the use of actual customer records.
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Supports scalable testing with dynamically generated datasets.
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Sample Use Case 2: Machine Learning Model Training Use Case
Scenario: Providing Large-Scale Data for AI/ML Model Development
Business Challenge:
A healthcare research company needed large volumes of medical records to train its AI-driven diagnostic model but was restricted by HIPAA compliance and data privacy regulations.
Solution with PDI Synthetic Data Generator:
- Generates synthetic patient data that mimics real-world cases while ensuring anonymity.
- Balances class distributions to create diverse datasets for machine learning models.
- Preserves statistical properties, allowing accurate model training without violating privacy laws.
Benefits:
- Ensures compliance with data privacy regulations such as HIPAA and GDPR.
- Accelerates AI model development by providing instant access to large datasets.
- Improves model accuracy by offering diverse and high-quality synthetic data.
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Sample Use Case 3: Regulatory Compliance Use Case
Scenario: Creating Privacy-Compliant Datasets for Auditing and Analysis
Business Challenge:
A fintech company needed to share customer transaction data with third-party auditors while complying with GDPR and other privacy laws.
Solution with PDI Synthetic Data Generator:
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Supports multi-region compliance, ensuring data usage aligns with different regulatory frameworks.
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Generates anonymized financial datasets while preserving transaction patterns.
- Maintains data consistency and integrity, ensuring auditors receive meaningful insights.
Benefits:
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Eliminates privacy risks by replacing real customer data with synthetic alternatives.
- Reduces compliance overhead by automating data anonymization and generation.
- Facilitates secure data sharing across partners and auditors without legal concerns.
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Feedback From Customers
Rodolfo Reopell
Senior Director of Business Intelligence and Analytics – STERIS Corporation
“A large-scale IDMC migration can be daunting, but PDI made the process remarkably smooth. PDI demonstrated exceptional flexibility, adapting to our needs and exceeding our Project timelines. This agility was crucial in ensuring a smooth transition without impacting our ongoing operations.
What truly impressed us was PDI's unwavering commitment to delivering results. They went above and beyond to address any challenges that arose, ensuring the project stayed on track and met our objectives. We're incredibly grateful for PDI's expertise and dedication throughout the implementation. PDI played a pivotal role in successfully modernizing our Informatica PowerCenter to IDMC, setting us up for a future efficient and scalable data management.”
