Traditional data quality best practices and tool functions still apply to big data, but success depends on making the right adjustments and optimizations.
- By Philip Russom
- April 19, 2019
Data quality issues become even more important as machine learning use grows. DataOps and data wrangling help enterprises address this vital problem.
- By James E. Powell
- April 16, 2019
Machine learning applications are dependent on, and sensitive to, the data they train on. These best practices will help you ensure that training data is of high quality.
- By Greg Council
- April 15, 2019
Adding property rights to inherent human data could provide a significant opportunity and differentiator for companies seeking to get ahead of the data ethics crisis and adopt good business ethics around consumer data.
- By Richie Etwaru
- April 9, 2019
Thinking about three key aspects of the cloud can accelerate your adoption of the technology.
- By William McKnight
- April 1, 2019
Modernizing their data warehouse presented a host of problems for a Denmark media company.
- By Brian J. Dooley
- March 28, 2019
How to start using machine learning for your enterprise, how food retailers are using big data, and how behavior studies can affect AI research.
- By Upside Staff
- March 26, 2019
Early adopters of the data lake have arrived at a maturation stage where they need to modernize their platforms before expanding their implementations.
- By Philip Russom
- March 15, 2019