Access Control for Distributed Data

Access control for data is much more complicated now that folks are not just using Hadoop with the HDFS API. Though the Hadoop community has made some very specific decisions on how they will facilitate data access via the HDFS API. Mike will explore and apply the broader Apache communities approach of the HDFS API access control lists. We will apply and then compare this to several use cases for compliance and broader security. He will cover the broader Apache community and why it has chosen to depart from other Apache projects like Sentry and Ranger. He will also cover examples of where these other tools are not sufficient. Attendees, should plan on leaving with some practical hands on steps to take in their own environments to provide better more secure data access.

Mike is a former IBMer where he co-founded IBM healthcare transformation lab. The Lab was a center for healthcare integration and analytics. His work includes genomic research of the HIV virus, gene ontology specifically for food plants in agriculture. Mike, founded a nonprofit to promote Urban agriculture and the data science behind food production. He has worked with NGO's, heads of state and presidential cabinet members helping them learn and understand the next generation Agriculture and food supplies. He is now working with the electronic frontier foundation to develop new licences for providing and keeping data open and free. He is active in the the Chicago hacker/maker movement and logs many of his creative hours at Workshop 88 in the Chicago Suburbs.