Azure is arguably one of the best cloud computing platforms in terms of security. Using it with platforms like Sonrai, you can safeguard your cloud infrastructure against potential cyber threats and vulnerabilities. Azure and Sonrai can perform better than Azure alone for your cloud ecosystem.
Azure Security Center offers several tools and capabilities to secure your cloud infrastructure. One of these tools is the Azure Purview, which was launched in December 2020 to facilitate data governance.
In this article, learn how to ensure data governance in your Azure system.
What is Data Governance?
Different sources define data governance differently in their context. So, you’ll likely get different meanings, too.
DAMA-DMBOK (Data Management Body of Knowledge) defines data governance as exercising your authority and control for managing the data assets.
The process ensures the accuracy and truthfulness of data. With an increase in AI or Artificial Intelligence initiatives, executives are striving for advanced, AI-driven environments and operations. But these next-generation technologies rely on accurate data.
Azure-based data governance ensures the accuracy you may need for AI implementation.
How to Ensure Data Governance?
There are multiple practices you can implement for data governance, but some are more critical than others. Here, they are:
- Centralize Control of Cloud and On-premise Data
If your organization uses hybrid cloud architecture to run your business, start with centralizing control of both on-premise and cloud data. Get complete control over all of your data assets. When you store your data on cloud services like AWS and Azure, they take some data control away from you. This isn’t a good practice for data governance.
But you can centralize your data to gain access to all of your critical assets. This is the foundation for data governance. When you manage data from a centralized location, there will be fewer conflicting authorizations and security policies. It will also enable different teams to move data on shared cloud platforms without violating data governance.
- Create Scalable, Global Data Policies
Just like governments use policies to govern their citizens, you need policies to govern your data. After you’ve centralized it, create a global policy.
These policies will govern how incoming data is treated. As you grow, you’ll be dealing with more data. Checking these manually is an insurmountable task. Data governance policies will help you manage the information automatically.
Also, you should make the policies global. This way, you can exchange data with platforms located anywhere in the globe.
- Grant Self-Service Access to Users
The data catalogs are designed to compile all the data into a single platform. This makes it easier for users to search, discover, and analyze data.
Your data governance policy should include the self-service capability. The users will then access available data and make modifications whenever needed. Also, they will get proper permission to do so. This process is more efficient than manually requesting access from the data owners.
- Automate Discovery of Sensitive Data
An organizational database on the cloud may include generic and sensitive information. You should take extra precautions for sensitive data. One of the ways is to allow sensitive data discovery. This is an automated way of discovering sensitive files. Once the files are detected, the system automatically tags them and applies appropriate access control policies.
That’s when you need to use a third-party, specialized cloud security platform like Sonrai. Azure and Sonrai together can safeguard your sensitive data in a much better way.
These specialized cloud security platforms connect to the Azure APIs and analyze the data stored in centralized environments. Based on the analysis, they classify the sensitive data.
- Create Faster Data Request Workflow
Discovering sensitive data is not all. Instead, you also need to certify it. Your DevSecOps team has to certify that the data has been detected, classified, and tagged appropriately. To achieve this, data architects can create workflows to approve the results of the automated sensitive data discovery process. Ideally, this process should take less than a minute and not days or weeks. Wasting valuable time on this process is a bad data governance practice.
Also, when the users request to access a data source, it should take seconds to authorize the request. So, develop a simplified data request workflow. It allows the team to quickly approve the requests and get users the resources they need.
Azure is a highly versatile, practical, and secure cloud platform for developing apps and running your business. But with third-party platforms like Sonrai, you get the most out of it. So if you’re using Azure and Sonrai together, you can optimize the returns on your investment.