Pitfalls in privacy data wrangling - Innovando.biz - España y América Latina

Fairy tales most often start with sentence: “Once upon a time there was a …” - Facebook?! Does any of you remember mobile app named “Foursquare”? It was very popular until a Russian-based developer used it to display “girls around me”. Data is a resource. Big data is a big resource. But - a big responsibility as well. It brings opportunity and it make threat. In world today we witness a steady rise of privacy concern and user awareness about what is right and what is wrong. Not only that, but regulations around the world guarantee certain rights to data subjects or consumers. Cambridge Analytica Ltd is very good example of Facebook data wrangling misuse or one could call this “data breach”. Careless use of meshed data or during company merge collecting data together from different anonymized sources into one data lake might be a potential serious risk for new organization. Can you imagine number of data collected over past decades on UK servers based on R&D under EU regulation? As we experience Brexit all the data wrangling using this meshed data raise legal ground question for further processing and secondary use. Privacy by design and by default is a key to proof accountability and key points we will discuss during talk are: • Data wrangling core ideas of discovering, structuring, cleaning, enriching, validating and publishing during data life cycle stages: collection, processing, disclosure, retention and destruction • How to secure enterprise data wrangling using GDPR and NIST as a privacy framework?