How to structure your BigQuery resources

What are folders, projects, and datasets and how do they come together to support warehousing fundamentals like security and cost management? In this episode of BigQuery Spotlight, we’ll review the BigQuery resource model and how this resource hierarchy is reflected in the Cloud Console, where you’ll interact with and analyze your BigQuery data. Moreover, we’ll give you some helpful tips when it comes to structuring your own BigQuery resources. Watch to learn the best way to structure your BigQuery deployments!

Timestamps:
0:00 - Intro
0:34 - Google Cloud Resource Hierarchy review
2:13 - How resource hierarchy is reflected in the Cloud Console
3:04 - Pricing
3:50 - Model where resources specific to BigQuery
5:05 - Common BigQuery resource structures
7:02 - Recap and summary

#BigQuerySpotlight

Product: BigQuery, Cloud Console; fullname: Leigha Jarett;

[pukjwgw]

Using standardised terminology would seem more intuitive. 2:22 - why call a database a project? For the uninitiated it can get very confusing when terms are ambiguous or mean different things depending on the context.

[MichaelDouglas-keth]

From a business perspective, how should datasets be logically organized? Is it a bad idea to break up datasets by client (1 dataset for each client)? Or should datasets be organized by business department (marketing, finance, etc)? Any resources/directions/best practices here would be appreciated! Thanks!

[ibrahimguzelbaba]

On 5:15, Common Storage Project and Compute Projects are mentioned. Are they named differently because of their intended use, or are there any differences in creation?