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This pipeline architecture was modeled using real-world business logic inspired by the operations of one of my favorite coastal restaurants to dine at on vacation, Baja Beach Cafe in San Diego, California.
The raw data simulation tracks some of their signature high-volume items -including fish tacos, specialty burgers, and margaritas - representing a true, fast-paced restaurant point-of-sale logging problem.
To test my pipeline under realistic business conditions, I deliberately engineered a simulated 'dirty' dataset filled with common point-of-sale anomalies. I then executed a custom Python function via the Mac terminal to automatically audit, clean, and reformat the chaotic data into a pristine structure.
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