This second session explores the topic of replatforming your legacy tooling to be ready for modern data science and AI. To succeed in AI, in addition to implementing new capabilities, you need to retire technical debt and bring all contributors in a unified environment. We will discuss:<\/p>\n
Key considerations when you decide to replatform
\nArchitecting for the era of AI \u2013 talent, technology, process and business
\nDiversity of tools for diverse talent \u2013 visual data science, programmatic data science and other tooling
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