Implement Data Processing and Baseline Forecasting Model

Implement the data ingestion and preprocessing components of your Kubeflow pipeline. Write Python code to load historical consumption, weather, economic, and operational schedule data. Clean, merge, and feature-engineer this data for time-series forecasting. Then, build a baseline time-series forecasting model (e.g., Prophet, ARIMA, or a simple neural network) and encapsulate it as a Kubeflow Pipeline component. Provide unit tests for your data processing steps.