Using Azure Data Factory for Blob Deletion
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You have an Azure subscription that contains an Azure Storage account.
You plan to implement changes to a data storage solution to meet regulatory and compliance standards.
Every day, Azure needs to identify and delete blobs that were NOT modified during the last 100 days.
Solution: You schedule an Azure Data Factory pipeline with a delete activity.
Does this meet the goal?
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Explanations
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A. B.A
You can use the Delete Activity in Azure Data Factory to delete files or folders from on-premises storage stores or cloud storage stores.
Azure Blob storage is supported.
Note: You can also apply an Azure Blob storage lifecycle policy.
https://docs.microsoft.com/en-us/azure/data-factory/delete-activity https://docs.microsoft.com/en-us/azure/storage/blobs/storage-lifecycle-management-concepts?tabs=azure-portalThe solution of scheduling an Azure Data Factory pipeline with a delete activity will partially meet the stated goal of identifying and deleting blobs that were not modified during the last 100 days.
Azure Data Factory is a cloud-based data integration service that allows you to create, schedule, and orchestrate ETL/ELT workflows. The Delete activity in Azure Data Factory allows you to delete data from a specified location, such as Azure Blob Storage, based on certain conditions. You can configure the Delete activity to delete data based on file names, file types, and last modified dates.
In this case, you can create an Azure Data Factory pipeline that includes a Delete activity to delete blobs that were not modified during the last 100 days. You can configure the Delete activity to use a filter expression that identifies blobs that have not been modified in the last 100 days and delete them.
However, this solution does not fully meet the regulatory and compliance standards requirement. The solution only addresses the requirement of deleting blobs that have not been modified in the last 100 days. It does not address other regulatory and compliance requirements, such as data encryption, access control, data retention policies, and auditing.
Therefore, while scheduling an Azure Data Factory pipeline with a Delete activity is a step in the right direction, it may not be sufficient to fully meet the regulatory and compliance standards. Additional measures may be required to ensure that the data storage solution complies with the regulatory and compliance standards.
