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This video tutorial demonstrates how to identify issues in a time series dataset and prepare it for ARIMA modeling. The data used is from Google Trends, comparing the search frequency of "ice-cream" and "heater." The focus is on the search frequency for "heater," which has been increasing steadily since 2004. The presenter will provide the data and code on GitHub for reference, emphasizing the importance of data preparation before feeding it into ARIMA models.