Developers & Practitioners

BigQuery Admin reference guide: Recap

Over the past few weeks, we have been publishing videos and blogs that walk through the fundamentals of architecting and administering your BigQuery data warehouse. Throughout this series, we have focused on teaching foundational concepts and applying best practices observed directly from customers. Below, you can find links to each week’s content:

  • Resource Hierarchy [blog]: Understand how BigQuery fits into the Google Cloud resource hierarchy, and strategies for effectively designing your organization’s BigQuery resource model.

  • Tables & Routines [blog]: What are the different types of tables in BigQuery? When should you use a federated connection to access external data, vs bringing data directly into native storage? How do routines help provide easy-to-use and consistent analytics? Find out here!

  • Jobs & Reservation Model [blog]: Learn how BigQuery manages jobs, or execution resources, and how processing jobs plays into the purchase of dedicated slots and the reservation model.

  • Storage & Optimizations [blog]: Curious to understand how BigQuery stores data in ways that optimize query performance? Here, we go under-the-hood to learn about data storage and how you can further optimize how BigQuery stores your data.

Query Processing [blog]: Ever wonder what happens when you click “run” on a new BigQuery query? This week, we talked about how BigQuery divides and conquers query execution to power super fast analytics on huge datasets.

  • Query Optimization [blog]: Learn about different techniques to optimize queries. Plus, dig into query execution for more complex workflows to better understand tactics for saving time and money analyzing your data. 

  • Data Governance [blog]: Understand how to ensure that data is secure, private, accessible, and usable  inside of BigQuery. Also explore integrations with other GCP tools to build end-to-end data governance pipelines. 

  • BigQuery API Landscape [blog]: Take a tour of the BigQuery APIs and learn how they can be used to automate meaningful data-fueled workflows.

  • Monitoring [blog]: Walk through the different monitoring data sources and platforms that can be used to continuously ensure your deployment is cost effective, performant and secure.

We hope that these links can act as resources to help onboard new team members onto BigQuery or a reference for rethinking new patterns or optimizations - so make sure to bookmark this page! If you have any feedback or ideas for future videos, blogs or data focused series, don’t hesitate to reach out to me on LinkedIn or Twitter.