Google Cloud BigQuery is optimized for which type of analytics?

Google Cloud BigQuery is optimized for large-scale analytics and real-time data analysis. This platform is specifically designed to handle vast amounts of data efficiently, enabling users to run complex queries on datasets that can be petabytes in size.

The architecture of BigQuery allows for the execution of analytics queries at high speeds by distributing the processing load across multiple resources in a highly scalable manner. This capability is particularly beneficial for organizations that need to derive insights from significant volumes of data quickly, making it ideal for large-scale analytics.

Additionally, BigQuery supports real-time analytics through features like streaming data ingestion, which allows data to be analyzed as soon as it is generated. This enables businesses to make timely and informed decisions based on the most current information available.

Although batch processing and storage analytics are relevant aspects of data management, they are not the primary focus of BigQuery’s optimization. Instead, the platform's strength lies in its ability to quickly analyze extensive datasets while also providing functionality for real-time insights, thus establishing its key position in the realm of modern data warehousing and analytics.