AI-Powered Reinvention of Data Engineering
Details
Cette session sera en anglais/This session will be in English
Join us for a transformative discussion on how AI is fundamentally reshaping data engineering. As we move beyond the era of repetitive pipeline maintenance, AI is guiding the shift toward intelligent and adaptive system design. In this session, we’ll explore how AI assistants empower engineers to move beyond manually building and fixing brittle ETL workflows. Instead, teams collaborate with these advanced tools to generate, refactor, validate, and document code with greater speed and reliability.
We’ll delve into how prompts are becoming a crucial new layer of logic that demands the same rigor as traditional code, utilizing best practices like prompt versioning and constant evaluation. This reinvention of data engineering amplifies — not replaces — engineering discipline, enabling teams to build more adaptive, scalable, and resilient data platforms. Get ready to learn how focusing on higher-value architectural and analytical challenges can unlock new levels of efficiency and performance in data operations.Join us for a transformative discussion on how AI is fundamentally reshaping data engineering. As we move beyond the era of repetitive pipeline maintenance, AI is guiding the shift toward intelligent and adaptive system design. In this session, we’ll explore how AI assistants empower engineers to move beyond manually building and fixing brittle ETL workflows. Instead, teams collaborate with these advanced tools to generate, refactor, validate, and document code with greater speed and reliability.
We’ll delve into how prompts are becoming a crucial new layer of logic that demands the same rigor as traditional code, utilizing best practices like prompt versioning and constant evaluation. This reinvention of data engineering amplifies — not replaces — engineering discipline, enabling teams to build more adaptive, scalable, and resilient data platforms. Get ready to learn how focusing on higher-value architectural and analytical challenges can unlock new levels of efficiency and performance in data operations.
