Chapter 3: Introducing BigQuery Syntax
The BigQuery dialect is compliant with the standard ANSI 2011 and is quite easy to learn for people who know other dialects and have experience with SQL. The main differences in terms of syntax are represented by BigQuery extensions, which allow us to use advanced features such as Machine Learning (ML). Bringing ML capabilities into SQL allows different roles to access it. This approach has the clear goal of democratizing the use of ML across different functions within a company, generating as much value as possible. With BigQuery ML, Google Cloud is filling the gap between tech-savvy people with ML skills and business analysts who know the company's data very well and have been working on it for years.
To build your confidence with the BigQuery environment and its dialect, we'll go through the following topics:
- Creating a BigQuery dataset
- Discovering BigQuery SQL
- Diving into BigQuery ML
