Data Digest: Bias in Analytics, Data Lakes for Security, Data Lessons from 2016
How to reduce bias in data analytics, avoid issues with security-focused data lake projects, and learn from recent failures in predictive analytics.
- By Quint Turner
- January 9, 2017
Analytics seems impartial but can still perpetuate bias due to hidden biases within the humans who write the code or the data a model is trained with. This article offers tips on how to minimize that bias.
Read more at O'Reilly Media
One of the many applications for analytics is security. If your enterprise is struggling to use a data lake for security analytics, you are probably having problems with the first phases of implementation.
Read more at Dark Reading
Three major unpredicted events occurred in 2016 that went against beliefs in predictive analytics. The lessons your enterprise can learn from them about proper analysis are here.
Read more at Datanami
About the Author
Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.