Encoding Drift in Representation | Data Drift скачать в хорошем качестве

Encoding Drift in Representation | Data Drift

Encoding drift occurs when the meaning of data changes over time while its encoded form remains the same. This video provides an in-depth explanation of what encoding drift is, how it arises, why it is difficult to detect, and why it poses serious risks to analytics, machine learning, and decision-making systems. As part of the Data Explained series, this video focuses on representation stability, data drift, and the importance of monitoring meaning, not just format. Topics include semantic drift, comparability breakdown, drift detection strategies, versioned encodings, and professional practices for managing evolving data systems.