Data Security and Access Control in Google Cloud Platform

Data Security

Who has access to my data? How do I ensure its safety? What should I check to ensure the settings are correct?

We’ve answered literally hundreds of security questions from online retailers and financial institutions while implementing Google BigQuery into their projects. So we decided to share the answers to some of the most frequently asked questions with those to whom it may be useful.

How secure is data storage in Google BigQuery?

Google’s attention to data security is well known. Look at the facts:

So, does your corporate storage meet these safety requirements?

In any case, the only thing that data storage security guarantees is that one will gain access if you provide it. Now you probably want to know how to access permissions.

How do I control access to my data in Google BigQuery?

The Access to Google Cloud Platform can be granted both to users and applications.

  • For applications, access is granted to the service account and authorization works via keys in PKCS12 format:
  • permision for project
  • As for users, you can use different roles:
    • Viewer: can only view the data. This access is sufficient for users who need to view data and create reports;
    • Editor: can edit and change the data. For example, a user with this permission can create aggregated tables, or add data from external sources;
    • Owner: has full access to the account management, including adding / removing users and controlling their access permissions.

Access can be issued both at the project and dataset level. You can use it to delimit the access of coworkers to the data.


Access Configuration Recommendations

  • Set up a two-step verification for Google accounts. In this case, even if an attacker manages to guess the password, they will not bypass the 2nd step of the verification process via phone.
  • Don’t use your personal Gmail address. You can register any email, including the one from your corporate domain, as a Google account. Use it in this way and recommend it to your colleagues as well.
  • Share the minimum reasonable access. Do not grant Editor access level to those users who need to create reports based on the data.
  • Keep access to sensitive data in different projects and different datasets. For example, user personal data or product margin are best kept separately with the limited access of those employees and applications that actually need it.
  • Do not save query results from Google BigQuery in CSV-format on your local drive. This increases the risk of data leakage in the event of losing your laptop or installing malicious software. Create reports directly in Google Sheets instead. All the data will be transferred to the Google Cloud Platform, and access will be controlled from your Google account.


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  • What security measures does Google Cloud Platform offers to ensure data privacy and protection?

    Google Cloud Platform provides a range of security features, including data encryption, access controls, firewalls, and monitoring tools to protect your data against unauthorized access, theft, and other vulnerabilities.
  • How can I control access to data in the Google Cloud Platform?

    You can control access to your data in the Google Cloud Platform by setting up identity and access management policies, role-based access controls, and assigning appropriate permissions to users based on their roles and responsibilities.
  • Is my data safe in the Google Cloud Platform?

    Yes, Google Cloud Platform takes extensive measures to ensure the security of your data, including physical, operational, and network security controls, data encryption, and continuous monitoring and logging of all activities.