A new TDWI Checklist Report examines best practices for data engineering and management to support machine learning with a focus on collecting, cleansing, transforming, and governing new and big data for analysis.
- By James E. Powell
- December 5, 2018
Enterprises need to make data governance a key part of their strategy in order to promote modern data-driven practices.
- By James E. Powell
- November 30, 2018
How AI can help enterprises address gender-based pay discrepancies.
- By Adam Zoia
- November 27, 2018
As society strives to master artificial intelligence, it is recognizing the need for explainable AI. This emerging trend will force organizations to create models that are effective and good for society.
- By Troy Hiltbrand
- November 26, 2018
Humans see less data as businesses collect more of it, which means we need something beyond data scientists.
- By Barry Devlin
- November 19, 2018
Delayed decisions mean delayed benefits. With data catalogs, everyone from data scientists to self-service BI users can benefit from useful information about their data.
- By James E. Powell
- November 15, 2018
Semantic knowledge graphs accelerate data engineering for machine learning, helping you maximize results.
- By Sean Martin
- November 9, 2018
These data quality best practices will both protect you and improve your marketing and customer contact.
- By Geoff Grow
- November 6, 2018