BigQuery, introduced by Google in 2010, serves as a serverless, cost-effective, multi-cloud data warehouse that allows scalable analysis of large datasets using SQL-based queries. It provides an interface for third-party developers to access features of Google's internal Dremel technology via a REST API, command-line interface, and web UI, maintaining high query performance. The tutorial detailed in the text guides users through the process of integrating Redpanda, a Kafka-compatible data streaming platform, with BigQuery via Kafka Connect, to enable real-time data streaming and analysis. It outlines steps to set up and configure Docker containers for Redpanda, create a dataset and table in BigQuery, and configure a Kafka Connect cluster to facilitate data flow from Redpanda to BigQuery. Users are also guided to run SQL queries on BigQuery to analyze data, including finding specific user interactions with classified ads, demonstrating the practical application of these tools in a data analytics scenario. The tutorial emphasizes the ease of streaming and analyzing large volumes of structured data in real-time, highlighting the usefulness of integrating Redpanda and BigQuery for interactive analytics and business intelligence purposes.