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.
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 BQML are great together in that Looker handles the data preparation and BQML 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 BQML capability to Looker Blocks.”
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.
BigQuery ML brings machine learning closer to where customers are storing large datasets, so they can quickly create and deploy models, at scale,” said Sudhir Hasbe, Director of Product Management, Google Cloud. “Looker’s integration with BigQuery ML adds powerful capabilities for our joint customers who can now use Looker to run ML models directly in BigQuery and surface the predictive insights across their organizations.”
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.
We have already been able to optimize our campaign performance across a number of marketing outlets using Looker and Google BigQuery,” said Nick Hardy, Data Scientist at Buzzfeed. “Now with Looker and the new BQML integration we can run predictive models directly in BigQuery using the Looker tools that we use every day. This could be a big time-saver for us. We look forward to implementing it.”
Sign up for the free insideAI News newsletter.
Speak Your Mind