Looker Enhances Data Science Capability with Integration for Google Cloud BigQuery ML

Looker, a leading data platform company, announced an integration with Google Cloud BigQuery ML (BQML) that reduces the time-to-value of data science workflows and allows business users to operationalize insights with interactive predictive metrics. With Looker and BQML, data teams can now save time and eliminate unnecessary processes by creating machine learning (ML) models directly in Google BigQuery via Looker – without the need to transfer data into additional ML tools. BQML predictive functionality will also be integrated into new or existing Looker Blocks allowing users to surface predictive measures in dashboards and applications. Looker Accelerates the Data Science Workflow. Looker provides a single, governed lens into an entire organization’s data. It accelerates the data science stack by removing the struggle to prepare data and freeing up time for data scientists to leverage ML at scale and use their unique skill set to perform higher-value tasks. Unified and cleaned data also delivers efficiency and clarity by quickly and accurately surfacing business insights for better context. Businesses can now move from data to decisions faster by leveraging leading analytic technologies to operationalize the outputs of ML models and take action instantly.