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betterdata Product Use Cases Industries Company Blog Get in touch Programmatic Synthetic Data that is faster, safer and fairer Transform your production data into privacy-preserving and highly realistic synthetic data. Share, access and build with data safely across teams, businesses, and international borders. Get in touch >How it works > Why betterdata The Pit Stop for Better Data: Synthetic Data Faster data, faster innovation Speed up and unlock access to sensitive data in days instead of months by reducing data compliance bureaucracy. Safer data with privacy by design Eliminate privacy risk of using or sharing sensitive data by replacing it with synthetic data that is legally compliant to data protection laws. Fairer data, fairer AI Identify and remove bias & imbalances in your data that leads to unethical AI models that breaks data protection laws and damages your brand's reputation. Anonymised data with maximum utility Use privacy-preserving synthetic data that preserves the structure and correlations of your original data instead of heavily anonymised data with huge information loss. Use Cases Enable your team to move faster and safer Product development and testing Replace sensitive production data or low quality dummy data in your product development and testing with highly realistic synthetic data to enable your team to iterate and innovate at speed. Data collaborations Data sharing drives enterprises innovation today but is a long and risky process. Whether it is third-party software testing or co-development of products with other companies & research institutes, replace sharing sensitive data with synthetic data to reduce the time and cost overhead of risk assessments by up to 70%. Data privacy verification Classic anonymisation techniques assumed to sufficiently protect data are often vulnerable to re-identification attacks. Our AI engine screens your data for potential threats to help you make a more informed decision on your most sensitive data and provide accountability to external auditors. Bias & imbalance mitigation Our synthetic engine enables intelligent data rebalancing such removing bias and imbalances. Removing bias will ensure your business use fair & transparent AI models that does not break any ethical AI regulations while imbalance correction leads to better performance of AI models. See more use cases >Have another use case? Let us know > Featured In Don't let data slow you down. Ready to incorporate synthetic data in your data strategy? Get in touch >Learn how it works > Subscribe to our monthly newsletter now! Stay in touch with the latest synthetic data advancements and use cases. betterdata PIXEL at One North (10 Central Exchange Green, Singapore 138649) [email protected] Follow us and keep updated! Product Why synthetic data? How it works FAQ Company About Contact us Careers Blog Privacy Policy Use Cases Product development & testing Data collaborations Data privacy verification Data retention Data monetisation Bias & imbalance mitigation Industries Financial Services Telecommunications Healthcare Retail © Copyright 2023 BetterData Pte Ltd - All Rights Reservedbetterdata Product Use Cases Industries Company Blog Get in touch How it works Schedule a demo > Generate and enhance synthetic data in 4 simple steps. 01 Real User Data Upload and preview a dataset from your computer or any connected database Training & Generation 02A Synthetic Data Engine Generate highly representative synthetic data that retains the same insights as your original data using state-of-the-art AI generative models 02B Differentially Private Learning Get proven privacy guarantees backed by mathematical proofs using Differential Privacy to enhance the protection of every individual training record 03 Rigorous Quality Assurance Measure the quality of the synthetic data using rigorous data utility and data privacy metrics for audit and compliance 04 Limitless Data Enhancement Out-of-the-box features to enhance your data including imbalance correction, bias reduction, 10x data augmentation for rare cases and intelligent filling of missing values in your original dataset The synthetic data generated looks, feels and functions just like your real data. Real data samples Synthetic data samples Frequently Asked Questions (FAQ) We're here to help. Can't find the answer to your question? Contact us here. Expand / Collapse All How is synthetic data generated? Synthetic data is generated using a combination of data processing pipelines and AI deep generative models such as GANs and autoencoders applied to tabular data. What data types are supported? We support tabular data (including dates, numbers, floats, categories) provided in an excel or csv file format. How large does the input dataset need to be? A minimum of 100 data rows. We would recommend at least 1000 - 3000 rows to achieve good generation. In general, the larger the dataset, the higher the quality of synthetic data generated. Is on-premise deployment supported? What infrastructure is required? We support on-premise deployment (air gapped environment not connected to the internet). ‍ Our models can run on CPU alone although we recommend GPU acceleration to speed up the AI model training and generation process. As a reference, a consumer grade GPU (e.g. Nvidia GeForce GTX 1080 Ti 11GB) takes 5 minutes to process a 10,000 row and 10 feature dataset. ‍ Is cloud deployment supported? Which cloud providers are supported? We support cloud deployment on any major cloud providers including Google Cloud Platform (GCP), AWS, Azure. betterdata PIXEL at One North (10 Central Exchange Green, Singapore 138649) [email protected] Follow us and keep updated! Product Why synthetic data? How it works FAQ Company About Contact us Careers Blog Privacy Policy Use Cases Product development & testing Data collaborations Data privacy verification Data retention Data monetisation Bias & imbalance mitigation Industries Financial Services Telecommunications Healthcare Retail © Copyright 2022 BetterData Pte Ltd - All Rights Reserved