By 2020, more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.
As an Enterprise Architect, much of what you do with your systems involves data. You strive to gain insight from that data to gain knowledge or a better understanding of your systems and their behavior, which allows you to make informed decisions. However, how you use data and extract a better understanding of systems can determine the level of success and competitive advantage.
The capability to transform data into actionable insight is the key to a competitive advantage for any organization. But the ability to autonomously learn and evolve as new data is introduced — without explicitly programming to do so — is the holy grail of business intelligence. That’s what ML offers: a capability that accelerates data-driven insights and knowledge acquisition.
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