Looker

Marketplace

Develop for Marketplace

Blocks

BigQuery ML Time-series Forecasting (ARIMA)

By Google
Build Explores that allow business users to create machine learning models for time-series forecasting.
Build Explores that allow business users to create machine learning models for time-series forecasting.

Version

v1.0.3

Release Notes

Category

Blocks

ETL Providers

N/A

SQL Dialects

Google BigQuery and BigQuery ML

Overview

Install this block for free by importing the project(s) from the GitHub repository linked at the top of the listing.

This is not an officially supported Google product.

Using this Block, you can integrate Looker with BigQuery ML Time-series (ARIMA Plus) models to get the benefit of forecasting with advanced analytics without needing to be an expert in data science. BigQuery ML ARIMA Plus model includes the following functionality:

  • Infer the data frequency of the time series
  • Handle irregular time intervals
  • Handle duplicate timestamps by taking the mean value
  • Interpolate missing data using local linear interpolation
  • Detect and clean spike and dip outliers
  • Detect and adjust abrupt step (level) changes
  • Detect and adjust holiday effects
  • Detect and adjust for seasonal patterns

This Block gives business users the ability to do time-series forecasting from a new or existing Explore. Explores created with this Block can be used to train multiple time-series models, evaluate them, and access their forecasts in dashboards or custom analyses.

Learn more in the associated BigQuery ML Tutorial.

Step by Step instructions for implementation are in the Block Readme

Related Content

Amazon Redshift Administration

GoogleFine-tune your Redshift deployment with a comprehensive view of performance and query analysis.Blocks

BigQuery Information Schema Performance Monitoring

GoogleMonitor and Explore your BigQuery Usage and PerformanceBlocks

© 2025 Looker Data Sciences, Inc.
Privacy | Terms | Cookies