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5 Benefits of Google Cloud’s New Security Blueprint for Data Warehouses

author Colin Van Dyke June 22, 2022

With so much development going on in the tech industry, companies are building tremendous assets on a daily basis, making security a worthy concern. It makes sense for Google to provide security tools for businesses that depend on its services for growth, traffic, and maintenance. Google has recently updated its Google Cloud security blueprints to make your cloud data extra safe.

Companies that use data warehouses to store data can do so with added security. At this security level, it’s necessary to have comprehensive protections for customer’s sensitive data. Since enterprises store this data in cloud data warehouses, high-level security during deployment is required to protect them from data breaches.

The Secure Data Warehouse Blueprint: What Is It?

Google Cloud provides a variety of services for enterprises, and it also provides a set of regulations, rules, and configurations that you can apply to strengthen security during cloud deployments. The Data Warehouse Blueprint is dedicated to helping companies safeguard their data while using artificial intelligence, machine learning, and data solutions provided by Google Cloud. 

This blueprint touches on these key components while keeping security and data governance in mind: 

  • Batch or streaming data is extracted into the landing area. 
  • De-identification of data and storage is set into the data warehouse component.
  • Encryption keys, data classification taxonomy, and the de-identification template are handled by the data governance and classification component. 
  • Monitoring, detection, and responses are provided by the security posture component. 


By following the blueprint instructions, you can securely deploy the needed components into your environment. Only the data presentation component which is outside the scope of this blueprint should be handled by your team. But what are some noticeable benefits of following this blueprint? Let’s check five of them.

1. Enhanced Business AnalysisO

Without having a solid knowledge of the best security practices for achieving data warehouse transformation, the process will be prolonged and challenging. By making use of the blueprint, you can implement the security patterns, code techniques, and the suggested practices on data governance. 

An essential part of the blueprint are the Infrastructure as a code (IaC) techniques which aid your teams in analyzing the controls and comparing them to the company’s requirements for operating the data warehouse and facilitating the compliance and regulatory reviews completed by the enterprise. 

Flexibility is also another strong point of this blueprint. You can either decide to keep the existing logging modules and existing network or set up a new initiative for deployment in the existing environment.  

2. Support of Layered Security Controls to Safeguard Data

The blueprint allows you to show the security, compliance, and risk teams the exact security controls utilized in the environment, and it sets up a minimalistic architecture accompanied by several built-in security controls. Different services combine together to increase the protection of your data. Some examples include: 

VPC Service Controls uses perimeters for grouping services by their functionalities, using perimeter bridges for data interchange and monitoring between perimeters. For instance, the data governance perimeter functions as a central location for monitoring and audit logging. It’s also used to control the encryption keys found in Cloud HSM, data classification taxonomy, and de-identification templates. 

The data ingestion perimeter de-identifies the data by relying on the de-identification templates combined with Dataflow and it finally stores the data into BigQuery. The blueprint explains other layers including the organization policies, networking, and IAM. 

3. Data Exfiltration Minimization

Security breaches like data exfiltration can be detrimental to your assets, and the blueprint allows you to monitor and define where data flows by deploying several VPC Service Control perimeters together with corresponding bridges. Through these perimeters data is limited to specific services and projects and the access is regulated depending on the context information provided by the Access Context Manager policies. 

The organization policies can be customized in addition to the restrictions that they provide to help you control access to data flow and other protective measures like restricting access from external IPs. The data in transit can flow safely through private connectivity to services and private networks. In cases when data is accessed unintentionally, you can employ the Cloud DLP configuration to de-identify the data with extra protective measures. 


4. Pervasive Data Warehouse Controls Configuration

The data warehouse security controls span over multiple resources and come into different modules. These modules help you explore various processes such as creating Cloud DLP de-identification templates, building Dataflow pipelines for re-identification or ingestion, and using BigQuery controls. Each module is customizable and can be tailored to match your specific requirements. 

Customer-managed encryption keys can be used to protect data for specific services. This leads to the creation of multiple keys, each with a tailored purpose. They function according to automatic rotation policy and are kept on the Cloud HSM. Their uses vary. For example, a key could be used to protect data residing within BigQuery or to deal with services concerned with ingestion. 

5. Compliance Needs Are Made Simpler

Relying on the blueprint allows you to handle data minimization with the Cloud’s cryptographic transformation methods. The latest implementation of automatic DLP for BigQuery has established a build-in capability that identifies unexpected types of data in the environment. Now, this integration gives further visibility access that aids the assessments in your environment.

Final Thoughts

The blueprint launch is accompanied by a deployable Terraform which you can access here. Working with data warehouses involves data security risks that if not addressed properly can lead to loss and corruption of data. Therefore, these blueprints provide excellent practices to help you stay safe. 

Blue Orange Digital is a certified partner of Snowflake and AWS and we can help you build and secure your data environments. Experienced in analyzing and storing data in cloud data lake environments, and in working with advanced tools, we can help you scale and secure your enterprise rapidly. Schedule a free 15-minute call with our team to learn more about what we offer.

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