Automating Data Quality Monitoring at Scale - Stanley, Jeremy; Schwartz, Paige
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In this book, Jeremy Stanley and Paige Schwartz from Anomalo explain how you can use automated data quality monitoring to cover all your tables efficiently, proactively alert on every category of issue, and resolve problems immediately.

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Produktbeschreibung
In this book, Jeremy Stanley and Paige Schwartz from Anomalo explain how you can use automated data quality monitoring to cover all your tables efficiently, proactively alert on every category of issue, and resolve problems immediately.
Autorenporträt
Jeremy Stanley is co-founder and CTO at Anomalo. Prior to Anomalo, Jeremy was the VP of Data Science at Instacart, where he led machine learning and drove multiple initiatives to improve the company's profitability. Previously, he led data science and engineering at other hyper-growth companies like Sailthru. He's applied machine learning and AI technologies to everything from insurance and accounting to ad-tech and last-mile delivery logistics. He's also a recognized thought leader in the data science community with hugely popular blog posts like Deep Learning with Emojis (not Math). Jeremy holds a BS in Mathematics from Wichita State University and an MBA from Columbia University.