Why Can’t ML Engineers Do Their Day Jobs? Hint: Crappy Data
Bogging down ML engineers with poor quality data that requires extensive manual processes impacts product quality and new feature speed to market.
In Data We Trust…After You Add a Little Blockchain
Blockchain can help ensure the success of IoT and AI by ensuring the trustworthiness and accuracy of the data being used by systems.
Naveego Tool Identifies Data Quality Issues in Minutes
Cloud service uses Hadoop and machine learning to find and fix issues in real time.
5 Tips for a Successful Machine Learning Deployment
Corporate educator TDWI has published an eBook on five engineering requirements for machine learning
MapR Extends Open Approach to Enterprise Data Quality
The MapR DataOps Governance Framework enables organizations to achieve a high level of data quality and integrity, and help meet mandated
Why Companies Need Data Validation
Some 40 percent of business initiatives fail due to poor-quality data. Michael Ludwig, chief product architect for Blazent, makes the case for data validation.