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Data Governance

Enabling enterprise-wide data privacy: Collibra + BigQuery

Most businesses are now taking a cloud-first approach to data and analytics. They opt for platforms like BigQuery for scalability and unified access. The unlimited computing power of cloud platforms can drive better business decisions with machine learning-driven analytics. Gartner Research predicts that cloud-native platforms will serve as the foundation for more than 95% of new digital initiatives by 2025.

Access control while moving data to the cloud

Organizations move data to the cloud to offer their users data access across silos. However, they need good access control to ensure that data usage is privacy-compliant. At the same time, they need to see that the data access is not excessively restricted to miss out on unlocking its value.

The traditional lift-and-shift migration does not work for controlling access to sensitive data. Collibra takes a more refined 3-step approach for moving data to the cloud. It enables you to define and enforce enterprise-wide data usage policies to manage access at a granular level.

The Collibra 3-step approach for moving data to the cloud:

  1. Data source registration to get a complete understanding of the enterprise data.
  2. Governed ingestion and transformation with the policies for using and retaining data.
  3. Governed catalog to identify the sensitive data, define the access controls, and centrally manage the data policies.

You can get more details of this approach in the Collibra white paper, Three key steps for successfully moving to the cloud.

Privacy-compliant access to sensitive data

As the landscape of data privacy regulations such as GDPR, CCPA, or CPRA evolves, managing access to data is becoming critical. Organizations want to protect sensitive data for regulatory compliance. But they also want to use the data for powering their business decisions.

The key reasons for moving data to the cloud are cost-efficient scalability and unified access. Though without the right access mechanism, the data in the cloud may get restricted to a select group, limiting the opportunities to unlock its value.

Collibra solves this dilemma by controlling access to data at a more granular level in the cloud with platforms like BigQuery. With Collibra, you can quickly identify protected data classes, such as PII and PHI. You can then label them and assign ownership. On the privacy front, Collibra makes it easy to define policies for data usage and map them to data. The data then has defined ownership and mapped policies. Systemizing your enterprise data while moving to the cloud prepares it for compliant use.

Collibra for enforcing enterprise-wide data access policies 

Once the data is prepared, the next step is managing the usage policies. You can use Collibra to document how data sets, data categories or specific classes of data can be used. After the data moves to the cloud, Collibra can provide a governed catalog with full data context including parameters on usage such as how it can be used, who it can be shared with, and how long it should be retained. This context can be pushed to Dataplex, providing data stewards and data owners with relevant information about appropriate data usage. Dataplex is Google’s intelligent data fabric that enables organizations to centrally manage, monitor, and govern their data across data lakes, data warehouses, and data marts. 

With Collibra, you are in total control of your data, processes, and policies. Consider you want to use BigQuery to create a quarterly report on orders. When you choose data sets, you find some of the data sets are classified as sensitive and restricted from use. It indicates that the information is protected and linked to a privacy policy. But you want to use the data set for your report and decide to request access for them.

Collibra gives you a self-service data shopping experience supported by streamlined processes. You can just add data sets to your basket, describe your purpose, and request access. Behind the scene, internal workflows route the request to the data owners. They review the policies and decide on the request. If the request is accepted, the data set will be available to you. 

This approach delivers data with the associated usage policies and the rightful data owners who can grant access. The compliant use of data helps you maximize the platforms like BigQuery without losing the intrinsic value of data.

Collibra embedded privacy by design uses data catalog and data governance to make sure that you always have compliant data ready for use.

  • Data catalog offers you the full context of data, along with ownership, lineage, quality, and usage policies.
  • Data governance helps you to identify sensitive data and enforce enterprise-wide policies for using it. If your data contains any PI or PII, it can be de-identified to make it privacy-compliant. Data governance also provides the required workflows for requesting access to the protected data.   

Collibra integrates directly with BigQuery services to enable enterprise-wide data privacy. Data consumers can choose the relevant datasets from BigQuery, request access through Collibra, and complete their analysis quickly.

Want to learn more about our three-step approach for moving data to the cloud?

Download the whitepaper!

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