Google BigQuery is a fully-managed, highly scalable, and cost-effective cloud data warehouse with built-in machine learning capabilities. It can analyze massive amounts of data in a short time, allowing businesses to leverage complex data for informed decision-making. Here are some advanced features of Google BigQuery that you should be aware of:

1. Federated Data Sources #

BigQuery offers the ability to query data directly from external data sources. This capability, known as federated data sources, allows BigQuery to access and analyze data in Google Cloud Storage, Google Drive, Cloud Bigtable, or even a spreadsheet in Google Sheets, without the need to load the data into BigQuery first.

2. Nested and Repeated Fields #

BigQuery supports complex data types, including nested and repeated fields. This allows you to store and query multi-valued properties and hierarchical data. You can use the STRUCT data type to define a nested record and the ARRAY data type to define a repeated field.

3. User-Defined Functions (UDFs) #

BigQuery enables you to create User-Defined Functions (UDFs), which are pieces of code that extend the standard SQL functionality. You can use JavaScript to write these functions and can include them in your SQL queries.

4. ML Integration #

BigQuery ML allows you to create and execute machine learning models within BigQuery using standard SQL queries. It supports a variety of ML models, including linear regression, logistic regression, k-means clustering, and neural networks, among others.

5. Geographic Information Systems (GIS) #

BigQuery GIS brings the power of spatial analysis to your data warehouse. It allows you to analyze and visualize geospatial data within BigQuery by using SQL to write geographic queries.

6. Data Transfer Service #

BigQuery Data Transfer Service automates data movement from SaaS applications to Google BigQuery on a scheduled, managed basis. This includes data sources like Google Ads, YouTube, and Google Play, among others.

7. Streaming Data #

BigQuery allows for real-time data ingestion by streaming data into your data warehouse. This ensures your data is always up-to-date and allows for real-time analytics.

8. Partitioned and Clustered Tables #

BigQuery provides the ability to partition and cluster your tables to optimize your queries and reduce costs. Partitioning allows you to divide your table into segments, while clustering reorganizes your data based on the contents of specified columns.

9. Security and Compliance #

BigQuery follows Google's stringent security and privacy policies. It also supports compliance certifications like ISO/IEC 27001, HIPAA, and EU GDPR among others.

By leveraging these advanced features, organizations can maximize their use of BigQuery to drive data-driven insights and decision-making.