BigQuery Admin Reference Guides with Leigha Jarett

Your hosts Stephanie Wong and Alicia Williams talk about BigQuery Admin Reference Guides with guest Leigha Jarett. Leigha tells us a bit about the origins of the Admin Reference Guide, which was developed to address frequent customer questions. The series of guides and videos covers onboarding topics from resource hierarchy and APIs to BigQuery tables and storage in an effort to help new admins get started.

The team's Reference Guide on tables helps admins understand the difference between federated and native tables, and Leigha tells our listeners some tips for using each type. Slots and reservations for workload management in BigQuery can be challenging to understand, but these Reference Guides and accompanying videos offer clear explanations. Optimizing projects for speed and monetary efficiency are important topics for any client, and Leigha and the optimization team have addressed these concerns as well. Tips for monitoring, data governance, and the secure sharing of data are also included in their video series, BigQuery Spotlight.

We wrap up with a discussion on BigQuery APIs and how easy it is to integrate BigQuery and other Google products.

Leigha Jarett

Leigha is a developer advocate on the Google Cloud Data & Analytics team. She focuses on making sure developers using tools like BigQuery and Looker are getting the most possible value from their data.

Cool things of the week

• Analyze Cloud Spanner data in BigQuery with federated queries docs
• Release notes dataset in BigQuery docs and XML feed
  • Google Cloud release notes docs and XML feed
  • Release notes in Cloud Console site
  • Top 25 Google Search terms, now in BigQuery blog

Interview

• BigQuery Admin Reference Guide Blog Recap site
• BigQuery Admin Reference Guide blog posts site
• BigQuery Spotlight Video Series videos
• BigQuery site
• BigQuery Documentation docs
• Cloud Spanner site
• Data Catalog site
• Apps Script site
• Looker site

What's something cool you're working on?

Alicia is building new BigQuery architectures in order to understand the journey and identify potential pain areas that may need more support.