brewdata-dbt-Snowflake is an advanced integration framework that enables seamless synthetic data generation within Snowflake using dbt Core. This project simplifies data transformation and management by leveraging Python-based dbt models alongside the brewdata package. Designed for developers, analysts, and data engineers, it provides an efficient way to generate high-quality synthetic data for testing, development, and analytics.
Leverages dbt Core for streamlined data transformation and modeling.
Designed to work efficiently with Snowflake’s cloud-based data warehouse.
Supports a variety of standard and GAN-based data generation techniques.
Simplifies the configuration process for quick deployment.
Detailed guides and examples for effortless implementation.
This solution empowers businesses to test and develop data-driven applications securely by generating realistic yet anonymized synthetic data within Snowflake.
Github LinkRealize the Value of your Real Data by Turning it into Synthetic Data using Generative AI.
Get Extensive Reports about Utility, Frequency Distributions and Privacy Assurance on Demand!
You don’t need to be a Machine Learning Specialist or a Data Scientist to use our tools – Just Point and Click!
Assure Privacy with Masking, Redaction or Pseudonymizing; Adjust Frequency Distributions of Data; Validate your Synthetic Data with our Extensive Reports; Turn your Real Data into Production Ready Synthetic Data
Synthetic Data has the same characteristics as Real Data including Referential Integrity!
Generate GDPR, HIPAA Compliance Reports on Demand or Design and Create Your Own Custom Compliance Reports based on your own Criteria
brewdata Studio enables you to design and create your Synthetic Data with a Point and Click interface – No SQL or Scripts!
Traditionally Mocked-up Data does not always represent the Frequency Characteristics of Real Data sets.
More Features
Indicate Column Ordering For Primary Keys and Secondary Keys for Preserving Referential Integrity
Specify Constraints your Synthetic Data needs to Satisfy – Columns to be Synthesized; Complex Semantic Constraints it needs to satisfy; Statistical Distributions you want altered if needed
Run your Synthetic Data Generation Jobs; View Utility, Privacy Assurance Reports; Adjust Constraints, Volume of Data you desire and Rerun Synthetic Jobs
brewdata’s data generation algorithms create Synthetic Data with the same statistical characteristics of the original Real Data with point-and-click ease. You don’t need to be a Data Scientist! You can also use brewdata to alter these characteristics if you want to counter for lack of Diversity or Bias. Or include more Edge or Boundary Cases for software testing.
To understand how easy it is to use brewdata and how good the quality of Synthetic Data generated is, listen to what our clients say about us!
About UsWe wanted to unlock the value of all the Marketing Data we had. We could not even share them internally because of the Personally Identifiable Information (PII) in them. Brewdata gives us a way of making use of this information safely for planning our strategies and tactics.
We have a lot of sensitive data in our On-Prem data centers. We are also ramping up our cloud usage and are wary of having this data in public clouds. Brewdata allows us to create synthetic data within our on-prem servers. We can then move this data to the cloud and use them for financial, marketing and operational simulation.
Our company stores a lot of sensitive information including financial about our customers. A lot of this customer data was off limits to even internal software testing. Brewdata helped us create synthetic data out of them. It helped us keep essential characteristics of the data but deidentify any columns that held sensitive ones. This helped our internal testing efforts immensely.
Synthetic Data is of interest to us but risk of re-identification of real persons from it have always held us back from using serious use of them. Privacy Assurance reports that balance effort to create data with the level of privacy assurance afforded would allow us to make better use of Synthetic Data. Brewdata’s Privacy Assurance reports allowed us to do exactly that!
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