Angelo and Manos' connection began in the 265 Course at Harvard University on Big Data Systems. This course inspired Angelo's thesis. The two discuss Manos' papers and how the future of Big Data is on the boundaries of Moore's Law. If you think about LSM trees (Log-Structured Merge Trees) and compacting data, what is considered acceptable deletion when users ask for their data to be removed? Is it when the data is removed from the identifying user that is good enough? In the analysis of Big Data Systems, considerations are always towards performance. An extensive delete sequence will cause a significant disruption in the system. Most people would address the completion of current execution cycles, perhaps during non-peak hours, and flag the no longer valid data. Maybe it could be that your data starts to become dirty, then what? How do you solve issues like privacy and the request for the "Right to be forgotten" or the "Right to erase"?  

Manos speaks about the papers he has written, which you can read in the links below. He addresses the delete question and boundaries with privacy in mind.  Performance is a crucial factor, and looking at the issue holistically is just as important as encryption when protecting privacy.

Mano's Research Papers 

• https://dl.acm.org/doi/10.1145/3318464.3389757
• https://disc-projects.bu.edu/lethe/
• https://blogs.bu.edu/mathan/2020/06/29/lets-talk-about-deletes/

Further Reading

• CS265: Big Data Systems - Spring 2020
• Manos Athanassoulis homepage
• California Consumer Privacy Act - BCLP California Consumer Protection Act Information
• General Data Protection Regulation (GDPR) – Final text neatly arranged
• Fast 21 Chen Hao

Host: Angelo Kastroulis

Executive Producer: Náture Kastroulis

Producer: Albert Perrotta

Communications Strategist: Albert Perrotta

Video/Audio Engineer: Ryan Thompson

Music: All Things Grow by Oliver Worth