Member-only story
6 Best Practices for Managing Data Access to BigQuery
What to know in terms of security when setting up a data environment in BigQuery.
We have all seen and heard about data breaches and the damages, both in terms of financial and reputation, that they can inflict. As we rely more and more on our data to make better decisions, data is becoming a critical asset for any organization. So like any other asset of a company, controlling access to data is essential to protecting your data.
Fortunately, modern data warehouses have great functionalities built-in to control precisely who has access to what. This is often referred to as Identity and access management or IAM. Cloud providers often design multiple layers to control access to data, and this post aims to shed some light on how Google does it with BigQuery.
However, it can be challenging to know the best practices in controlling access with the many control layers. This post attempts to lay out some recommended practices that I have come across over the years.
How resources are organized in Google Cloud
BigQuery is Google’s technology of choice for data warehousing. To understand how to control access to BigQuery, you first have to understand how resources are organized in…
