The demo dashboard in Looker studio is not available.
Compatible with the following data sources:
Google Analytics 4
Google Analytics UA
Google Adwords
Microsoft Ads
Facebook Ads
DV360
What this report is about
Arima Plus forecasting report helps to analyze trends, seasonal patterns, and the relationship between current and past data to predict future data points in a time series.
What Arima Plus model is about
ARIMA Plus is like a weather forecast for your business data. Just as meteorologists use patterns from past weather data to predict tomorrow's weather, Arima Plus uses your past business data to predict future outcomes.
Here's what Arima Plus does step-by-step:
Understanding your data's rhythm: Every business has a rhythm or frequency. Maybe you get more sales during weekends or particular seasons. Arima Plus identifies this rhythm and automatically determines the frequency of your time series data.
Handling inconsistencies: If there are missing dates or duplicate entries in your data, Arima Plus fixes them. Arima Plus greatly handles irregular and non-uniform time intervals.
Spotting outliers: Just as one exceptionally rainy day doesn't define a season, a sudden spike in website traffic or sales doesn't define your general business trend. Arima Plus identifies and manages these unusual spikes, drops and abrupt changes.
Adjusting for holidays: Holidays can greatly affect business data. Arima Plus recognizes these patterns and adjusts for them.
Identifying trends: Arima Plus examines whether your business data is growing, declining, or staying the same over time. It uses the ARIMA model for trend detection and the auto.ARIMA algorithm for hyperparameter tuning.
Imagine you're trying to predict how a certain aspect of your business, like sales or website traffic, will perform in the future. The tool helping you do that is called a time series forecasting model. One of the most efficient tools for this job is ARIMA Plus, a feature provided by BigQuery.
How Arima Plus model works
ARIMA Plus is a time series model within BigQuery that's essentially an enhanced version of the traditional ARIMA model. It offers:
Advanced time series decomposition: Using STL (Seasonal and Trend decomposition using Loess), it can detect multiple seasonal patterns within a single time series.
Support for new training options: ARIMA Plus includes the DECOMPOSE_TIME_SERIES training option.
Improved functions: It supports table-valued functions like ML.ARIMA_EVALUATE and ML.EXPLAIN_FORECAST.
Parallel training: You can forecast up to 100,000,000 time series simultaneously.
How to use this report
To benefit from the Precis starter report, you need to follow these steps: