PwC: On GDPR and the Future of Regulations
We talked to Rémi Dusaud, Director of Data Privacy at PwC, about what the landscape is like now and what’s to come.
learn moreWith the heightening challenge given the influx of new data regulations being drafted, not to mention upkeep of processes that ensure continued compliance with existing legislation, things start getting complex quickly in terms of governance.
But compliance cannot exist on the technical level alone; true compliance and respect for data regulations is a mindset that must be embedded throughout the organization. Besides mitigating legal risk, collaboration across all the teams that engage with or benefit from users’ data is critical for larger success.
Since most developers and analysts are not lawyers, the majority of teams involved in data usage will not have the expertise needed to understand whether a particular action is compliant or not. Through education, restrictive admin rights, and broken-down silos, teams can distribute expertise and still uphold compliance.
Data compliance is all about asking questions and building time into project lifecycles to get the answers. While the nature of legislation suggests a lack of room for interpretation, understanding key facts about data before it is used is critical to ensuring compliance.
Dataiku is the centralized data platform that enables the creation of Enterprise AI projects while also providing the tools for data regulation compliance. Dataiku ensures more opportunities for business-impacting models by providing a solid foundation for data governance policies that allow teams to work faster, smarter, and more securely.
Enterprises using Dataiku can better prepare themselves for current — or future — data regulations with the capacity to:
The age of AI presents additional risks across the enterprise that require a tighter — yet more flexible — governance structure.
Read moreWe talked to Rémi Dusaud, Director of Data Privacy at PwC, about what the landscape is like now and what’s to come.
learn moreWhat it is, why it matters, and how to develop ML models in a way that is consistent with sound MLOps practices — all brought to you by Dataiku and O'Reilly.
get the white paperDespite the hype, most companies still have not dedicated the time and effort to ensure models are deployed responsibly.
learn moreThis guidebook walks through the myths & realities of working with personal data, working with anonymized data, and pseudonymization.
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