Solve data access and provisioning with Synthesized & BigQuery
Access to compliant and privacy-preserving snapshots
Automatic data rebalancing, upsampling and filling out missing values for development and testing purposes. High-quality data generation for functional validation, performance, and integration testing.
Data generation and subsetting
Generation of high-quality data that preserves statistical properties of original data and is free of sensitive PII/SPI data.
Accelerating cloud migrations
Create reusable data transformation workflows to shorten data collection lead time. Iterate, set up and test ML pipelines with Airflow, GCP Cloud Composer, Dbt, Spark and others ETL tools whilst waiting for the lengthy original data access procedures.
The Synthesized Solution
Quick access to data snapshots enables faster and compliant data insights
The integration of Synthesized SDK and Google BigQuery offers multiple avenues to leverage its capabilities, providing organizations with flexibility to choose the approach that aligns with their specific requirements.
Fast access to a compliant snapshot
A compliance projection of the data for testing and development purposes.
Simplifying model training
Programmatically create diverse data snapshots that cover a wide range of scenarios, including edge cases and rare events. This diversity helps improve the robustness and generalization of machine learning models.
Creating full datasets
For unbalanced data, when an original dataset is incomplete but analysis requires the extrapolation of additional reliable data points.
Accelerating and evaluating cloud migration
with accurate test data that mimics the structure of cloud databases, so you can confidently add sanitized or synthetic data by extending existing CI/CD pipelines.
Run SDK on Google Cloud
Synthesized Scientific Data Kit (SDK) is now available on Google Marketplace
