Why Data Quality Begins At The Source

MAD Data: An ML, AI, and Data Podcast by Databand - Un pódcast de Databand

Databand.ai Director of Product, Shani Keynan, provides a fresh perspective on how to define data quality and how to control data quality when your data is in motion. Data observability is well understood to be a means to quality data. However, what's often overlooked is the sheer distance that data must travel from the moment it's collected all the way to data consumers. This means that data observability must be performed truly from end-to-end by starting right from the beginning (at the data ingestion layer) in order for data observability to be effective at all. Shani offers examples that illustrate how to make data quality an achievable goal and how to apply real-world logic and context create business impact.

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