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825: Data Contracts: The Key to Data Quality, with Chad Sanderson
Super Data Science: ML & AI Podcast with Jon Krohn
Integrate Data Quality into Development Workflow
The concept of 'Shift Left' in data management mirrors its origins in security, advocating for the integration of data quality and governance requirements directly into the development processes of software engineers. This proactive approach addresses data quality issues at the source, ensuring that developers understand the implications of their code changes on downstream data usage, particularly for data scientists. By embedding checks for data quality issues into the coding workflow—like monitoring changes in data attributes such as timestamps—teams can prevent potential disruptions in machine learning models and analytics. Collaborative communication between data producers and users is essential, enabling timely adjustments and optimizations before code is deployed, ultimately fostering a culture of shared responsibility for data integrity.
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