When writing code, test driven development is a common accepted methodology to ensure the development of high quality software. Your organization’s data, on the other hand, is an entirely different challenge. Data can be missing due to human error, a failure with a 3rd party provider, a botched release, or dozens of other issues. When not missing, data can still become corrupted or start exhibiting a trend in the wrong direction that isn’t obvious to notice.
Anomalo is a complete data quality platform. It can monitor your enterprise data and alert you to problems that are automatically detected. In this episode, I interview Jeremy Stanley about the ways in which teams are using the platform to monitor and improve their data quality.
The post Data Quality Using Anomalo with Jeremy Stanley appeared first on Software Engineering Daily.
