From Data to Insight: Infusing your Enterprise AI with IBM Watson Machine Learning for z/OS

 

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Kewei Wei (魏可), Senior Technical Staff Member, Lead Architect of IBM Watson Machine Learning for z/OS, IBM China Development Lab

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Guanjun Cai, Senior Information Architect and Developer of IBM Watson Machine Learning for z/OS and Db2 for z/OS, IBM Silicon Valley Lab

 

The rapid growth in digital data will continue on an upward trajectory into the next decade. According to David Reinsel in “The Digitization of the World”, an IDC white paper sponsored by Seagate, “the Global Datasphere will grow from 33 Zettabytes (ZB) in 2018 to 175 ZB by 2025” and the datasphere in China alone, for example, will expand at the rate of “30% on average over the next 7 years.” [1] The vast volume of data promises enterprises unprecedented opportunities in the data-driven economy but challenges them to integrate artificial intelligence (AI) and machine learning in their IT operations. AI and machine learning are already reshaping the industries. Gartner predicts that the global enterprise value derived from AI will total from $1.2 trillion in 2018 to $3.9 trillion in 2022 [2].  The quicker enterprises apply AI and machine learning to the data they amass, the sooner they will be able to extract actionable insight and derive business value from it, ultimately disrupting their competition and gaining market advantage.

 

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