Gretel And BigQuery DataFrames For Generating Synthetic Data
Gretel allows users to easily create synthetic data from prompts or seed data, which is perfect for unblocking AI projects
Google Cloud offers a synthetic data generation feature in BigQuery with Gretel, allowing users to expedite development timeframes by minimizing or doing away with friction
A strong and smooth way to create and use synthetic data right inside your BigQuery environment is to integrate Gretel with BigQuery DataFrames
Gretel and BigQuery DataFrames work together to accelerate innovation, improve data accessibility, and reduce privacy issues while enabling enterprises to realize the full value of their data
Both your project environment and Google Cloud house data: Both your project and BigQuery continue to safely store your original data
Data access is made easy using BigQuery DataFrames, which offer a familiar pandas-like API for loading and modifying data inside your BigQuery environment
Synthetic data is produced by Gretel’s models, which can be accessible via their API and are used to create synthetic data from the original data in BigQuery