Systems | Development | Analytics | API | Testing

Join us for an exciting session into the newly announced BigQuery ML, a capability inside Google BigQuery that allows data scientists and analysts to build and deploy machine learning models on massive structured or semi-structured datasets.

Join Developer Advocate Felipe Hoffa and the the CTO of Nomanini - Dale Humby - to learn more about how they use App Engine, Kubernetes, BigQuery and other GCP tools.

This lab explores some of the bigger concepts and smaller work required to migrate data from an existing (on-premises) data warehouse solution to GCP.

In this video, Lak Lakshmanan, Tech Lead, Professional Services, shows you a new feature that makes analyzing and visualizing geospatial data in BigQuery easy and highly performant. BigQuery GIS provides a convenient, powerful way to incorporate spatial information in your decision making.

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.