BigQuery is a data warehouse for large volumes of data.

Bigquery for Big Data

Scale and speed are two notable features of Google’s BigQuery. It's designed for ease of use with SQL and offers integration with various data transfer and machine learning tools. It’s designed for businesses wanting to analyse big data with a pay-as-you-go pricing model.

Google Analytics and BigQuery

Bringing Google Analytics data into BigQuery can help you reveal business insights across more data. You can export all event data from Google Analytics to BigQuery for free. In BigQuery, you can import external data from other sources, like CRM data, and combine it with your Google Analytics data. This enables you to build audience segments, explore custom traffic attribution, and build simple ML models for reporting and audiences

Machine Learning (ML)

BigQuery ML enables us to build ML models on structured, semi-structured, and unstructured data, generating business insights and predictions. For example forecasting the sales of an item on a given day, anomaly detection, or creating a product recommendation system.

Other Options

Other options include AWS Redshift, Azure Synapse Analytics, and Snowflake. If you are already using a particular cloud platform to store your data, it could make sense to use that provider’s data warehouse and analytics platform.