Build a query-ready lakehouse with Fivetran, Apache Iceberg and Google’s Cloud Storage
May 21, 2025
9 AM – 10:30 AM PST
Virtual
David Hrncir
Coral Trivedi
Bruce Sandell
Vinod Ramachandran
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In this 90-minute hands-on lab, you’ll learn how to quickly build a fully operational lakehouse architecture on Google Cloud, leveraging Fivetran’s Managed Data Lake Service and your Cloud Storage data lake. We’ll show you how to seamlessly centralize structured and unstructured data from over 700 sources into Google's Cloud Storage (GCS) — and make it instantly queryable with Apache Iceberg, BigQuery metastore, and Looker’s conversational analytics.
We'll walk through:
- Ingesting data into GCS with high-performance, fully managed pipelines including automatic conversion to open table formats.
- Connect BigQuery metastore to automatically catalog your data for seamless querying.
- Querying tables using open formats like Apache Iceberg.
- Analyzing data in Looker with natural language, skipping the SQL.
You’ll leave with a modern data lake architecture that supports open table formats, cataloged metadata, and a cost effective data foundation that’s ready for AI/ML workloads and enterprise-scale governance. This is your fast path to building a modern, fully queryable, AI-ready lakehouse without stitching it together yourself.
David Hrncir
Coral Trivedi
Bruce Sandell
Vinod Ramachandran
David Hrncir
Coral Trivedi
Bruce Sandell
Vinod Ramachandran
In this 90-minute hands-on lab, you’ll learn how to quickly build a fully operational lakehouse architecture on Google Cloud, leveraging Fivetran’s Managed Data Lake Service and your Cloud Storage data lake. We’ll show you how to seamlessly centralize structured and unstructured data from over 700 sources into Google's Cloud Storage (GCS) — and make it instantly queryable with Apache Iceberg, BigQuery metastore, and Looker’s conversational analytics.
We'll walk through:
- Ingesting data into GCS with high-performance, fully managed pipelines including automatic conversion to open table formats.
- Connect BigQuery metastore to automatically catalog your data for seamless querying.
- Querying tables using open formats like Apache Iceberg.
- Analyzing data in Looker with natural language, skipping the SQL.
You’ll leave with a modern data lake architecture that supports open table formats, cataloged metadata, and a cost effective data foundation that’s ready for AI/ML workloads and enterprise-scale governance. This is your fast path to building a modern, fully queryable, AI-ready lakehouse without stitching it together yourself.