To that end, Google has announced a beta release of BigQuery ML, a SQL-based extension to its enterprise data warehouse service, for building and deploying machine learning models.

With Looker Studio and BigQuery SQL, Google will surely keep the "Jenga pieces" of business intelligence from falling apart. Learn how you can join our contributor community.

Since BigQuery became available to all developers in 2012, it’s been possible to query data with the SQL-like BQL, which stands for BigQuery Query Language.

Users can use SQL queries and their existing SQL tools and skills without knowing ML-specific programming skills and ML frameworks. Google's goal with BigQuery ML is to democratize machine ...

BigQuery vs Snowflake: Which ETL tool is best? Your email has been sent ETL tools can help you gain more actionable insights from your data sets across multiple sources. Read this comparison of ...

An SQL-Based Platform Requiring Specific Expertise With BigQuery, you need SQL to access and make the most of your data. You therefore need to make SQL queries or have someone in-house to do it ...

Google has rolled out a new beta of BigQuery, the data warehousing and analysis service available on Google Cloud Platform, which lets admins use standard SQL instead of one of its dialects.

BigQuery originally did not resemble a typical data warehouse, as it worked best when data is organized in nested structures that, at first blush, look more like JSON documents than typical SQL ...