With the increasing importance being placed on ethical AI, organizations are turning more to “explainable AI” -- a set of processes and methods that allow them to understand the output of machine learning algorithms.
- By Mark Do Couto
- February 22, 2024
Supporting faltering data governance programs, governing data for AI, and problems with untrusted financial data.
- By Upside Staff
- February 22, 2024
Tips for new data scientists, why the U.S. Department of Agriculture is implementing a data science training program, and how AI is changing the job market.
- By Upside Staff
- February 20, 2024
Thanks to AI, next-generation data observability tools will extend beyond identifying problems and explain how to resolve the problem. To do so, your data platforms will need these three key features.
- By Eric Chu
- February 20, 2024
Fern Halper, Ph.D., vice president and senior research director for advanced analytics at TDWI, talks about the six pillars of data governance for artificial intelligence -- including transparency and ethics.
- By Upside Staff
- February 15, 2024
Practical tips for getting your AI program off the ground and new research that may point to ways to reduce the amount of training data ML needs.
- By Upside Staff
- February 13, 2024
James Kobielus, TDWI’s senior director of research for data management, talks about how to update your data management practices to prepare for the next generation of AI.
- By Upside Staff
- February 6, 2024
From AI/ML and the composable enterprise to advances in quantum computing, there are plenty of changes ahead for analytics. Here are particular areas to watch.
- By Ariel Katz
- February 5, 2024