Analytics

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.

Today we'll unpack how three of the world's largest producers of data - Oath, Spotify, and Twitter - leverage Google BigQuery for their essential analytics needs.

In this session we’ll discuss various options and best practices to implement BigQuery as a central data warehouse for your enterprise. Topic will include best practices for data storage, slot allocation, data access policies, project hierarchy, etc.

Learn how the top research universities are utilizing tools such as Google Compute Engine, BigQuery, and preemptible virtual machines to drastically reduce the time from idea to discovery, run millions of simulations at lightning-fast speed, and scale research capabilities with ease.

In this session, we willl talk about the high level data architecture at Traveloka, Southeast Asia's leading online travel company. There are many existing solutions for big data analytics, both offered as managed services or open source. At Traveloka, we are going as serverless as possible.

Join us for an interactive workshop in which we'll lead you through deploying a complete data analytics application, from collecting events from a web/mobile app, all the way to processing streaming data and getting the insights promptly.

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.