Tech insight Policy quarterly update - Q1 2023 Quarterly update on the latest developments in data policy and privacy for 2023 By Diana Sofronieva
Tech insight What makes synthetic data privacy-preserving? Why Hazy incorporates differential privacy to create privacy preserving synthetic data By Diana Sofronieva
Tech insight The latest development in the PETs space Part one of our Data Privacy series, an update on the regulation of Privacy Enhancing Technologies By Diana Sofronieva
Tech insight Chatting with ChatGPT about synthetic data Interview with an AI chatbot about the FAQs on synthetic data, adoption, privacy, and regulation By Georgi Ganev
Tech insight Regulation and Risk Management of AI in Financial Services 2022 - Highlights and key takeaways from the event Our key insights from the Regulation and Risk Management of AI in Financial Services Summit By Max Wybrow
Tech insight One Month at Hazy Continued perspective from an onboarding Machine Learning Engineer By Brian Cechmanek
Tech insight Multi-table synthetic data Hazy now supports synthesis of complex multi-table schemas By Edwin Onuonga & Emile Joubert
Tech insight Apply Differential Privacy with caution or you could bias your synthetic data While privacy might be the greatest concern, applying Differential Privacy blindly might lead to gen… By Georgi Ganev
Tech insight Hazy named a 2021 Gartner® Cool Vendor in AI Governance and Responsible AI Hazy is redefining the way businesses use and access their data whilst putting the customer data pro… By Harry Keen
Tech insight Is synthetic data safe? Learn how our ML algorithms create synthetic data without compromising privacy By James Arthur
Tech insight Hazy synthetic data quality metrics explained Synthetic data generation is proven to be a better way to protect data privacy while preserving util… By Armando Vieira
Tech insight What is synthetic data? Learn how synthetic data enables firms to innovate without privacy risks By Harry Keen
Tech insight The Beauty of GANs: Sharing insights without sharing data Generative Adversarial Networks or GANs are the most forward-thinking machine learning framework tha… By Armando Vieira
Tech insight How to generate sequential, time-series synthetic data We share a way to dramatically increase the fidelity of sequential and time-series synthetic data. By Jennifer Riggins
Tech insight Generating synthetic data with referential integrity using GANs Most organizations want to get value out of consumer data, without risking customer privacy. By Armando Vieira
Tech insight How Hazy uses deep learning models to create synthetic datasets The generative adversarial network or GANs is changing the way we build on deep learning and is driv… By Johnny Kelsey
Tech insight Synthetic scooter journeys: How synthetic data and differential privacy work Using Hazy to generate synthetic geographical data By Emile Joubert
Tech insight How synthetic data bridges data science and traditional engineering Silos are dangerous to modern financial orgs. Understanding synthetic data can build collaboration b… By Armando Vieira
Tech insight Python implementation of synthpop Reimplementation in Python of the R package synthpop, a tool for producing synthetic data containing… By Georgi Ganev
Tech insight Business insight Anonymised Data What is data anonymisation, how do you put it to use and what are its strengths and weaknesses as a … By James Arthur
Tech insight Business insight Anonymisation vs Pseudonymisation vs Synthetic Data Comparison and analysis of the pros and cons of anonymisation, pseudonymisation and synthetic data a… By James Arthur
Tech insight Data anonymisation - what, why and how? Data anonymisation is a set of processes and methods applied to a dataset in order to ensure that da… By Sofiane Mahiou
