Synthetic Data for AI: Definition, Risks, and Strategies
ABSTRACT :
Many machine learning projects fail because data scientists don’t have the right data. Techniques such as synthetic data is a novel algorithmic approach...
Read More
Register now for - "Analytics for Power Users: Practices and Products You Need to Know" - Wednesday, December 13, 11:30 a.m. Eastern Time.
ABSTRACT :
Many machine learning projects fail because data scientists don’t have the right data. Techniques such as synthetic data is a novel algorithmic approach...
Read MoreABSTRACT :
Data Stewardship Experience strategies can meet several needs and remove the stigma of data governance as a rigid and bureaucratic gatekeeping discipline.
Read MoreABSTRACT :
Consider key trends and challenges as you design an effective organizational architecture for data governance while generating value with pervasive...
Read MoreABSTRACT :
This article outlines how and why data engineers perform tests on their work efforts as they use automated testing and monitoring tools.
Read MoreABSTRACT :
This article describes how a data quality management framework helps data engineers create reliable data pipelines, data stores, and data lakes.
Read More