The success of data analytics is dependent on the availability of quality data, which can be difficult or expensive to acquire. Supplementing authentic data with synthetically generated data can improve the effectiveness of Analytics, Business Intelligence, and Product Development.
Can we apply Synthetic Data to Data Lakes?
Traditional analytics are limited to highly structured data. However, the 21st century enterprise possesses Data Lakes - mountains of structured and unstructured data, within loosely organized collections from disparate sources.
The potential of Data Lakes can now be tapped thanks to advances in Artificial Intelligence and Machine Learning. Applying Synthetic Data to Data Lakes allows engineers to get the most out of advanced Data Lake analytics.
What is the advantage of FlexGAN?
Current Synthetic Data Generation services are restricted to limited data types and schema. FlexGAN's proprietary framework provides an autonomous solution for the generation of Data Lakes of arbitrary schema and type. FlexGAN adapts to the unique structures of user provided data, mimicking the relationships and distributions found between collections of data within the entirety of the Data Lake.
FlexGAN generates synthetic data lakes that imitate real distributions and relationships found within and between your data sources.
Our cutting-edge machine learning technology powers FlexGAN's proprietary synthetic data generation framework. Check out our White Paper for an introductory tutorial on relational synthetic data generation.Read Our White Paper
Simply upload a Data Lake, and FLexGAN does the rest. Optionally provide input to customize synthetic data to your specification.
"More toward the cutting edge of machine learning, researchers and entrepreneurs are working on a set of innovations to reduce the amount of real-world data needed to train models and to enhance the value of existing datasets. One of the most promising of these is synthetic data, a technique that allows AI practitioners to artificially fabricate the data that they need to train their models. As synthetic data increases in fidelity, it will make machine learning dramatically cheaper and faster, opening up myriad new use cases and business opportunities." - Rob Toews
Contact us to schedule a free demo of the FlexGAN Synthetic Data Generation Service. Our demonstration features a fully functional prototype of the FlexGAN cloud service, complete with a user-interface for easy Synthetic Data generation and delivery.
The FlexGAN team has released a free open-source Python library with a suite of tools for generating synthetic relational data. The library will offer a glimpse of the capabilities provided through the FlexGAN service for Synthetic Data Lake Generation. Contact us to get updates on the release.
The FlexGAN team is currently developing a cloud-based subscription service to offer the complete FlexGAN solution for effortless Synthetic Data Lake generation through a user-interface and API. Please contact us for more information on FlexGAN.