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Data Quality Monitoring in AWS SageMaker

First things first, what is data quality monitoring? Data quality monitoring for machine learning can generally be thought of from two perspectives. One perspective is that of traditional data-engineering. This type of monitoring is concerned with the “physical” characteristics of the data and ensuring they are what you expect them to be. It involves criteria […]

General

Accurate by Design: Advanced Data Quality on AWS

Introduction Data pipelines in AWS orchestrate the movement and transformation of data across various AWS services. The core objective of these pipelines is to enable efficient data processing, analysis, and storage, ensuring that data is available where and when it is needed. Maintaining high data quality throughout this process is critical; it ensures reliability, accuracy, […]