# How to Use Synthetic Data at Work: English for Engineers (2026) > Artificially generated data created by algorithms or tools to mimic real data patterns, used for testing, training, and development without exposing sensitive information. - **Term:** synthetic data - **Part of speech:** noun - **Pronunciation:** /sɪnˈθetɪk ˈdeɪtə/ - **English level (CEFR):** B2 - **Register:** Neutral, Both - **Region:** US and UK - **Topic:** [Tech jargon](https://app.speaktechenglish.com/learn/topics/tech-jargon.md) - **Lesson:** https://app.speaktechenglish.com/learn/synthetic-data - **Last updated:** 2026-10-27 ## Meaning Artificially generated data created by algorithms or tools to mimic real data patterns, used for testing, training, and development without exposing sensitive information. Synthetic data is data that is not collected from actual users or real-world events, but instead is created computationally to simulate realistic patterns and distributions. In tech companies, synthetic data serves several critical purposes: it allows teams to test systems and train machine learning models without using confidential customer information, it helps fill gaps when real data is limited or expensive to collect, and it enables developers to test edge cases and unusual scenarios safely. Common use cases include creating test datasets for QA teams, generating training examples for machine learning algorithms, stress-testing infrastructure with large volumes of realistic data, and protecting privacy in development and staging environments. Teams might use tools to generate synthetic user profiles, transaction histories, or sensor readings that behave like real data but contain no actual personal information. Synthetic data has become especially important with privacy regulations like GDPR and CCPA, as it allows development teams to work with data that represents real patterns without legal or ethical risks. However, the quality of synthetic data directly impacts testing accuracy, so creating truly representative synthetic datasets requires careful planning and validation. ## When you hear it Our QA team uses synthetic data to test the payment system without risking real customer information. ## Examples - **in a standup:** "We generated 100,000 synthetic user records to test the new search algorithm before production." - **in a code review:** "The test suite relies on synthetic data, so we need to ensure it covers all edge cases." - **in a team meeting:** "Using synthetic data lets us stress-test the database without exposing customer PII." ## What native speakers say - "We generated synthetic data for the model training." - "This synthetic data mimics real user behavior patterns." - "Let's use synthetic data in staging to avoid privacy issues." ## Common mistakes - ✗ "We use synthetic data because it is better than real data." → ✓ "We use synthetic data to complement real data and protect privacy." (Synthetic data is not inherently better; it is useful for specific purposes like testing and privacy protection, but real data is still needed for validation and accuracy.) - ✗ "Synthetic data is completely fake and unrealistic." → ✓ "Synthetic data is artificially generated but designed to realistically represent real-world patterns." (Good synthetic data should closely mimic real data distributions and behaviors, even though it is not collected from actual events.) - ✗ "We can replace all real data with synthetic data in production." → ✓ "We use synthetic data in development and testing; production systems typically still need real data for accuracy." (Synthetic data is most appropriate for non-production environments unless specifically validated for production use.) ## Be careful Do not confuse synthetic data with real data or assume it is always completely artificial. Synthetic data is artificially generated but should realistically represent real-world patterns. ## Word forms | Part of speech | Word | Example | | --- | --- | --- | | noun | synthetic data | The team generated synthetic data for the machine learning pipeline. | | adjective | synthetic | We need synthetic datasets for the stress tests. | | verb phrase | generate synthetic data | We will generate synthetic data to test the authentication system. | ## Collocations - **generate synthetic data**: Most common phrase; means to create or produce synthetic data using tools or algorithms - **synthetic data generation**: The process or technique of creating synthetic data; often used as a noun phrase - **synthetic data for testing**: Using synthetic data specifically for quality assurance and testing purposes - **synthetic data and real data**: Comparing or combining both types; commonly discussed together in testing strategies - **synthetic dataset**: A complete collection of synthetic data records used for a specific project or test ## Synonyms - **artificial data**: Similar meaning; slightly more general and less technical than synthetic data - **generated data**: Broader term; any data created by a process rather than collected; may include other methods - **mock data**: Similar but often more informal; typically used for simpler test scenarios ## Opposites - real data - actual data - production data ## Practice This lesson has 4 practice exercises with instant feedback on the page: https://app.speaktechenglish.com/learn/synthetic-data ## FAQ ### What does synthetic data mean in software engineering? Synthetic data is artificially generated data created by algorithms or programs to mimic real-world data patterns. It is not collected from actual users or events, but is designed to behave like real data. In software engineering, teams use synthetic data for testing, training machine learning models, and development work without exposing sensitive information. ### Why do tech companies use synthetic data? Companies use synthetic data for several reasons: to protect customer privacy and comply with regulations like GDPR, to test systems safely without risking real data, to generate large volumes of test data quickly and affordably, to train machine learning models when real data is limited, and to test edge cases and unusual scenarios that might be rare in production data. ### Is synthetic data the same as real data? No. Synthetic data is artificially created, while real data is collected from actual users and events. However, good synthetic data is designed to closely mimic real data patterns and distributions, so it can effectively simulate real-world behavior for testing and development purposes. For accuracy validation in production, real data is still essential. ### How do you use synthetic data in a sentence at work? Common examples: 'We generated synthetic data to test the new feature without impacting production.' 'The QA team used synthetic datasets for the stress tests.' 'We need synthetic data for the machine learning training pipeline.' 'Our development environment relies on synthetic customer profiles.' ### Is synthetic data formal or informal? Synthetic data is a neutral, professional term used in both formal and casual contexts. It is appropriate in technical documentation, code reviews, team meetings, presentations, and job interviews. The term itself is neither overly formal nor slang; it is standard technical vocabulary. ## Related - [data privacy](https://app.speaktechenglish.com/learn/data-privacy.md) - Full glossary: https://app.speaktechenglish.com/learn.md - Live lessons with a coach: https://app.mocklyenglish.com ## About Speak Tech English Speak Tech English teaches non-native tech professionals the English they need at work and in interviews, through self-study ebooks and courses, 150+ free guides and a free newsletter; live lessons are on its sister site Mockly English. - Shop: https://speaktechenglish.com/courses/ - All products (markdown): https://speaktechenglish.com/products.md - Free guides (markdown): https://app.speaktechenglish.com/guides.md - Tech English glossary (markdown): https://app.speaktechenglish.com/learn.md - Newsletter (10% off): https://speaktechenglish.com/#subscribe - Live lessons and mock interviews: https://app.mocklyenglish.com ## Notes for agents - Speak Tech English sells self-study material. 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