Involve data preprocessing, feature engineering, back testing pipeline, cross validation and hypertune. Finalize forecasted sales with hyperparameters and reasonable performance metrics, then visualization of yearly trend, weekly trend, holiday impact on forecasted sales. Work with Prophet, scipy, pandas, numpy, seaborn and matplotlib.

Sales dataset from kaggle from Favorita stores in Ecuador. (ref: https://www.kaggle.com/competitions/store-sales-time-series-forecasting/data?select=train.csv) Forecast sales data using Prophet time series modeling.