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Mar 2019 - IDC Perspective - Doc # AP43909019

From Cottage Industry to the Production Line: Productivity Tools for Machine Learning

By: Thomas JingAssociate Market Analyst, Jessie Danqing CaiSenior Research Manager, Christopher Lee MarshallAssociate Vice President

Abstract

Long viewed as troublesome prelude to modelling, data engineering increasingly is becoming the essential component for developing an effective machine learning and data science capability. Therefore, not surprisingly, appearing are tools and platforms that support the data discovery, extraction, manipulation, loading, and transforming, which take the lion's share of the average data scientist's daily work. These tools include automated machine learning platforms, visual coding toolkits, data virtualization platforms, and in-database machine learning tools.


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