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How I Built a Data Pipeline with AI Report Automation
Integrating API, DuckDB, Price Optimization, and AI report automation
Introduction
Since the publication of "Data Scientist: The Sexiest Job of the 21st Century" in the Harvard Business Review in October 2012, the field has continued to grow. Naturally, as this is a wide area, the focus has changed a few times, with Analytics, Machine Learning, Deep Learning, and now Artificial Intelligence (AI) being the center of attention.
In the last couple of years, the absurd amount of data generated each day made the question “what to do with all that data?” pop up, thus turning part of that attention to another important area in the data field: Data Engineering.
It also fed (and keeps feeding) the hungry Large Language Models (LLMs), making possible the tremendous advances with AI. Now, we’re experimenting and learning what AI agents can do for us, and so many cool things pop up every day.
Certainly, as I love learning new tech skills, I don’t want to be out of that, so I keep experimenting and learning about AI Agents too.
In this post, we will deep dive into a data pipeline powered by AI reporting skills.
Come with me.
