How can I create a forecasting model for seasonal sales trends in BigQuery?

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How can I create a forecasting model for seasonal sales trends in BigQuery?

Asked on Dec 26, 2025

Answer

Creating a forecasting model for seasonal sales trends in BigQuery involves using SQL queries to analyze historical data and apply statistical methods to predict future trends. This process typically includes data preparation, applying time series analysis, and visualizing results.

Example Concept: Use BigQuery's SQL capabilities to perform time series analysis by first aggregating sales data by time intervals (e.g., monthly or quarterly). Apply statistical functions such as ARIMA (AutoRegressive Integrated Moving Average) to model and forecast future sales trends. Utilize BigQuery ML for more advanced machine learning models to refine predictions based on historical patterns.

Additional Comment:

Ensure your dataset is clean and includes consistent time intervals for accurate forecasting.
Consider using BigQuery ML's built-in time series functions for more sophisticated modeling.
Visualize your forecasted data using Looker Studio or other BI tools for better insights.

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