Topmost challenges that data warehouses have faced over the years are coping with storage requirements for ever-growing data and increased demand for compute to process this data. Google Cloud Platform has enabled creation of a completely serverless, scalable, flexible, and resilient data warehouse at Vuclip.

In this session, we'll explain how your analytics data is stored in BigQuery and then show you some important tips on working with this data as we create queries to answer your burning mobile analytics questions.

In 2017, Tapjoy migrated Vertica and Hadoop from our on-premises data center into Google Cloud BigQuery and Google Compute Engine. We'd like to share our journey and lessons learned on migration to BigQuery and GCE.

Using examples from the finance and retail industries we will walk through the core products in GCP data platform. The session will cover BigData analytics services such as: BigQuery, Dataflow, Pub/Sub, Dataproc, Dataprep, Datalab, and Datastudio.

Are you ready to take your knowledge of SQL to its final frontiers? Join this session to learn how you can use BigQuery and its SQL 2011 compliant features to tap deep into insights locked away in your spreadsheets, JSON files, and other semi-structured data formats.

This talk, by one of the founders of the BigQuery team and a founder and current CTO of Looker, will make the case that BigQuery is not just another Enterprise Data Warehouse. It will show how BigQuery's unique properties follow from its technical architecture.

Predictive Analytics with BigQuery ML.

Many large organizations build custom dashboards and reporting around their cloud usage to track that usage across teams and applications, and to understand cost drivers. In this session, the Billing team and Vendasta will show you how to export your detailed billing data to BigQuery, write useful queries around that data, and create custom dashboards based on those queries in Data Studio.

This talk will focus on how BigQuery and Looker allowed a small data team at Buzzfeed to manage the data needs of 800 users, and how migrating from AWS Redshift to BigQuery gave us the performance we needed to allow interactive querying of large datasets by non-technical people.

In this session, we will show the common failure points and how you can build scalable, interactive, insightful dashboards in Data Studio from BigQuery data.