Join DMZ Europe
Expect a lot of interesting speeches and workshops at Data Modeling Zone Europe 2017. Data Modeling Zone is an annual conference in the US and in Europe where you can sharpen your data modeling skills, share experiences with other data professionals, and help shape our data modeling industry. DMZ Europe contains over 30 sessions crossing five tracks. Learn from top data experts in the world, as well as many experts in the fields of data science, NoSQL, facilitation, and enterprise architecture.
Subscribe and visit Aveve’s presentation on DMZ US/EUR.
GDPR and Data Modeling: Our Journey
Annemie Van Cauter, Rebekka Moyson and Ivan Schotsmans
One of the main ideas at DMZ EU 2017 was that ‘GDPR was coming and it was going to bite us all in the arse’. The EU General Data Protection Regulation entered into force May 25th builds on the previous directive regarding data privacy, yet brings about new and more stringent obligations for companies dealing with personal information, as well as new and stricter rights for the PI holder, in addition to stricter enforcement. As a consequence, it is now essential to keep track of where personal data is situated in your company, what it is being used for, the retention rate, and whether consent was given for the processing activity, among others. This directive applies to all companies processing personal data of data subjects residing in the European Union, regardless of the company’s location.
Needless to say, GDPR carries a lot of new requirements.
So are you interested to hear whether the GDPR did bite us in the arse? This session will discuss the approach taken in our quest to become compliant, not only challenged by the limited amount of time left, but also by the severe complexity we face in our company (think activity in a variety of industries, over 50 business units, more than 10 information systems, …). Hence, this talk will guide you through our journey of building a data model with all the considerations and consequences involved, being guided by the methodology proposed by the full scale data architecture.