[Panel] Big Data Analytics vs Privacy: Risks and Opportunities - ERP Spain.com - España y América Latina

Using sensitive data for advanced analytics and machine learning is an effective mechanism for increasing revenue and building customer loyalty - among other benefits - but it comes with a set of considerations around utility and privacy, all of which need addressing: - How can you extract value from your sensitive data sets? - What privacy concerns should you consider? - Is encryption enough to protect your data when it is shared? Many organisations are sitting on vast amounts of sensitive, yet highly valuable data and are currently unable to maximise its value. That data could be shared with internal teams and third parties, but privacy concerns and compliance restrictions prevent the data from being utilised effectively. Unlocking the data’s true value is a challenge, but there are a range of tools and techniques that can help. This live discussion will focus on the data analytics landscape; compliance considerations and opportunities for improving data utility in 2018 and beyond. Key takeaways: - A view of the data protection landscape - Tools and techniques to unlock the value of your sensitive data - Considerations for moving data to the cloud and sharing it with internal teams and third parties - Opportunities for maximising data utility in 2018