Is synthetic data the key to greater data science use?

Data science teams want access to data and lots of it. They rightly argue that without prompt and unfettered access, their effectiveness is limited. The problem for organisations is that they have so much data that they struggle to clean it in order to allow such access. Most attempts to sanitise or anonymise data are anything but. The majority of solutions do pseudo anonymisation which takes little effort to reverse engineer.








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