Governance for Big Data Environments

August 16, 2021

Governance for Big Data Environments

Welcome to our post about cloud governance for big data environments, where we will compare and contrast some of the best cloud governance tools available in the market.

Data is the new oil, and with the rise of big data, organizations are faced with challenges regarding how to manage and govern their data. The need for cloud governance tools for big data environments has increased to ensure data security, compliance, and proper usage.

Azure Policy

Azure Policy is a cloud governance tool that helps organizations to create, assign, and manage policies. Policies are a set of rules and restrictions that enable organizations to govern their deployed resources. Azure policy can be used to audit and enforce policies on resources, resources groups, or entire subscriptions.

Cost: Free

AWS Config

AWS Config is a fully managed service that helps organizations to assess, audit, and evaluate their AWS resources. AWS Config enables organizations to create rules to evaluate AWS resources, track changes to resources, and audit changes across resources. It also provides a history of changes to the resources.

Cost: $2.00 per rule per month

Google Cloud Resource Manager

Google Cloud Resource Manager is a cloud governance tool that helps organizations manage and control their Google Cloud resources. It enables organizations to create, modify, and delete projects across the Google Cloud platform, and it also allows organizations to manage access controls to certain projects.

Cost: Free

Conclusion

In conclusion, Azure Policy, AWS Config, and Google Cloud Resource Manager are all great cloud governance tools for big data environments. However, the choice of which tool to use depends on the specific needs of your organization. Therefore, before choosing a tool, it is essential to evaluate each tool's capabilities and compare them to your organization's requirements.

We hope that this comparison has been helpful in your decision-making process.

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