Google’s BigQuery ML needs big changes to compete
When Google first released BigQuery ML, it was accompanied by much buzz, but experts said the suite of ML extensions has since been eclipsed by other automated machine learning platforms. Many are looking to the Google Cloud Next ’19 conference in San Francisco to see what updates are in store for BigQuery ML and how Google plans to keep pace in an increasingly competitive field.
At one anticipated session at Google Cloud Next, the tech giant is set to announce a host of new models and features focused on improving and simplifying BigQuery ML’s data science and machine learning capabilities. Google will be joined onstage by Booking.com, a customer that is expected to elaborate about its migration to BigQuery ML and how it’s using new models to assess data quality.
“I’m sure [Google] will focus on progress and try to highlight some enterprise-class customers who have migrated from rival deployments rather than developing new data warehouses from scratch,” said Doug Henschen, an analyst at Constellation Research. “I’d also expect more ties between BigQuery and Google deep learning and data science capabilities.”
Google did not immediately respond to an email requesting comment for this story.
Meanwhile, Google has touted a number of what it says are BigQuery ML’s advantages over other approaches.
Among them, according to Google, are enabling data analysts to build and run models using existing BI tools and spreadsheet; eliminating the need to program an ML model using Python or Java; and making model development faster by removing the need to export data from a data warehouse.
Lynne Baer, an analyst at Amalgam Insights, said she is looking forward to hearing from Booking.com, but still is somewhat skeptical that Google has advanced its platform enough to match those of competitors.
“I feel like Google’s BigQuery ML has fallen behind compared to some other players in the market like a DataRobot or an H2O Driverless AI,” Baer said.
Baer added that Google needs to collect more customer stories like Booking.com’s, including from users across more verticals. She said Google needs to make better arguments for using BigQuery ML in industries such as healthcare, financial services and government.
Introduced in 2011, Google’s BigQuery, an enterprise-grade data warehouse, is one of Google’s most mature cloud services. In July 2018, Google released its first beta version of BigQuery ML, new software attached to BigQuery. Google touted BigQuery ML as a tool for data analysts and data scientists to build select machine learning models using standard SQL commands — instead of advanced languages such as R, Python and Scala — without having to move data across platforms.
