Differential privacy is an interesting tool when doing privacy aware analytics. This is a topic I have been working on for a while, and one of the great challenges is to implement generic tools for this. However, developers at Google are using this a lot internally, and they have also made their libraries available at GitHub. Since I often prefer Python, I am happy to find a Python wrapper for the Google libraries from OpenMined at GitHub. They also provide some nice examples (with Jupyter Notebooks). See also the discussion in CACM «Differential Privacy: The Pursuit of Protections by Default» with the people at Google that have been central in releasing their differential privacy libraries to the public.