Looker Enhances Data Science Capability With Integration for Google BigQuery ML

WIRE)--Looker, a leading data platform company, today announced an integration with Google Cloud BigQuery ML (BQML) that accelerates the time-to-value of data science workflows and allows business users to operationalize insights with interactive predictive metrics. With Looker and BigQuery ML, data teams can now save time and eliminate unnecessary processes by creating machine learning (ML) models directly in BigQuery via Looker – without the need to transfer data into additional ML tools. BigQuery ML predictive functionality will also be integrated into new or existing Looker Blocks allowing users to surface predictive measures in dashboards and applications. "Much of the work in machine learning centers around data preparation and ML model evaluation and tuning," said Lloyd Tabb, Looker Co-founder, Chairman and CTO. "Looker and BigQuery ML are great together in that Looker handles the data preparation and BigQuery ML does the learning. Looker can also help you evaluate and tune ML models to integrate predictions into dashboards and data workflows. We look forward to continuing our work with Google and bringing BigQuery ML capability to Looker Blocks."