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Technical Vocabularynoun · /sɪnˈθetɪk ˈdeɪtə/

synthetic data

In simple English

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.

Definition and practical use cases of synthetic data in software testing, machine learning training, and privacy-compliant development.

At a glanceCEFR B2
Commonness4/5
Versatility4/5
FormalityCasualFormalNeutral
Spoken ↔ WrittenSpokenWrittenBoth
Directness ↔ DiplomaticDirectDiplomaticDirect
RegionUS and UK
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Say it like this

✓We generated synthetic data for the model training.
✓This synthetic data mimics real user behavior patterns.
✓Let us use synthetic data in staging to avoid privacy issues.

Real 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."

Don't say this

Handle with care. 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.

✕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.

Other forms

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."

Often used with

generate synthetic dataMost common phrase; means to create or produce synthetic data using tools or algorithms
synthetic data generationThe process or technique of creating synthetic data; often used as a noun phrase
synthetic data for testingUsing synthetic data specifically for quality assurance and testing purposes
synthetic data and real dataComparing or combining both types; commonly discussed together in testing strategies
synthetic datasetA complete collection of synthetic data records used for a specific project or test

Similar words

artificial dataSimilar meaning; slightly more general and less technical than synthetic data
generated dataBroader term; any data created by a process rather than collected; may include other methods
mock dataSimilar but often more informal; typically used for simpler test scenarios

Opposites

real dataactual dataproduction data

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Practice

Try it

4 quick exercises

Complete the sentence

1. We should _______ the payment system before launch to avoid risking real customer data.

Spot the mistake

2. Which sentence uses synthetic data correctly?

Pick the most natural phrasing

3. You need to explain why your team uses synthetic data. Which sounds most natural?

Rewrite naturally

4. Rewrite this using synthetic data naturally: 'We created information that is not real but looks like customer records so we could test the system.'

Questions

Quick poll

Have you said "synthetic data" in a standup this week?

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