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The DataOps Factory

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Abstract

Data science and analytics are in a broken state. A 2016 Klynveld Peat Marwick Goerdeler (KPMG) study of 2000 global data analytics decision-makers revealed that only 10% believe they excel in data quality, tools, and methodologies, and 60% say they are not very confident in their analytical insights.1 For every organization that finds measurable success from data science and analytics, several others struggle with data quality, the ability to get work into production, and generate meaningful ROI on investments in people or technology. DataOps is a cure for many of the problems facing data science and analytics today. By adopting DataOps, organizations can deliver data products in a consistent, reliable, fast, scalable, and repeatable process just like a factory.

Copyright information

© Harvinder Atwal 2020

Authors and Affiliations

  1. 1.IsleworthUK

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