Migrating and modernizing your cloud data warehouse can be long and complicated, requiring multi-year efforts involving multiple teams and tools. There are a few main challenges that companies face with migration, such as high TCO associated with data pipelines, connecting hybrid and multicloud environments, and a long path to analytics-ready data. At Confluent, we’re taking a different approach. Today, with Confluent, enterprises can stream data across hybrid and multicloud environments to Google Cloud’s BigQuery, powering real-time analysis while reducing total cost of ownership and time to value. In this webinar, you’ll join experts from Confluent and Google Cloud to explore real-time data and warehousing. We’ll discuss: Real-world use cases on how organizations are using Confluent Cloud and BigQuery to achieve their business goals How to stream data from Confluent to BigQuery via a connector for data queries, analytics, and dashboards How to containerize and run a data producer on Google Cloud which sends data to Kafka on Confluent Cloud How to perform queries on that data warehouse and stream process on Confluent Sam Bassey Customer Engineer, Google Sam Bassey is a Customer Engineer at Google where he focuses on enabling data analytics on digital-native accounts. He has been at Google for a little over seven months and, prior to that, worked in the consulting space, where he focused on data engineering. Elena Cuevas Elena Cuevas Senior Partner Solutions Engineer, Confluent Elena Cuevas is a Senior Partner Solutions Engineer at Confluent, where she focuses on the Google Cloud partnership. Before joining Confluent, Elena spent several years at Google working directly with some of the biggest Google Cloud customers.