Michael Williams uses sentiment analysis to show that supervised machine learning has the potential to amplify the voices of the most privileged people in society.
Perils of big data
Ideas and resources for understanding the perils of data.
Fangjin Yang and Xavier Léauté describe how they architected their analytics stack around Druid, and overcame the challenges around scaling the system, balancing features with cost, and making performance consistent.
Connecting data scientists with domain expertise makes more of the unknowns known.
Common pitfalls and best practices every manager should know.
How to prevent false positives from limiting intrusion detection systems
Daniel Goroff discusses recent mathematical ideas, like differential privacy, that offer new ways of reaching robust conclusions while protecting personal information.
Pitfalls to avoid when you're dealing with qualitative information.
It's time to tackle data's disposal problem. Maciej Ceglowski makes the case for adopting enforceable limits for data storage.
In the next decade, Year Zero will be how big data reaches everyone and will fundamentally change how we live.