This article describes how to rename a storage account in the Azure public cloud. Renames although not common arise occasionally as erstwhile resources are repurposed or have mistakes to be corrected. For example, use of prefixes and suffixes in storage account might change with repurposing or retargeting a different environment. One cannot rename an Azure storage account from the portal or any other way. If a different name were to be used for an existing storage account, a new one  would need to be created with the desired name and then the data moved and any associated configurations made to the new account. Connection strings or settings of any dependent resources may need to be updated as well.

Some additional information that might be helpful are:

• The new name for your storage account must be unique across Azure and follow certain naming restrictions.
• Renaming the storage account name can have benefits such as consistency, clarity, and accurate tracking of your storage usage.
• Renaming the storage account name can also have implications for the resources associated with it, so one should be careful and test the changes before deleting the old account.

Data transfer can be facilitated with a cloud service like Azure Data Factory or a downloadable tool like AzCopy. Azure Data Factory is a cloud-based data integration service provided by Microsoft Azure. It allows users to create, schedule, and orchestrate data pipelines that move and transform data from various sources to different destinations. Azure Data Factory supports data movement between on-premises systems, cloud-based systems, and hybrid environments. It also provides capabilities for data transformation, data orchestration, monitoring, and management of data pipelines. With Azure Data Factory, users can easily automate and manage their data integration and data transformation processes in a scalable and reliable manner.

Azure Data Factory can be used to copy data between various data stores and services, such as:

1. Copying data between Azure storage accounts: Azure Data Factory can transfer data between different Azure storage accounts, such as Azure Blob storage, Azure Data Lake Storage, and Azure File Storage.
2. Copying data between on-premises and Azure: Azure Data Factory supports copying data between on-premises data sources, such as SQL Server or Oracle databases, and Azure data stores. This allows organizations to move data from their on-premises infrastructure to the cloud.
3. Copying data between cloud-based data sources: Azure Data Factory can transfer data between various cloud-based data sources, including Azure SQL Database, Azure Synapse Analytics (formerly SQL Data Warehouse), and other Azure services.
4. Copying data between cross-cloud platforms: Azure Data Factory enables data transfer between different cloud platforms, such as Azure and AWS or Azure and Google Cloud Platform. This allows organizations to integrate and consolidate data from multiple cloud providers.
5. Copying data with transformations: Azure Data Factory supports data transformations during the copying process. It allows you to apply transformations, such as filtering, aggregating, or joining data, before transferring it to the destination.
6. Incremental data copying: Azure Data Factory can perform incremental data copying, where only the changed or new data is transferred, rather than copying the entire dataset. This helps optimize the data transfer process and reduce costs.
7. Fault-tolerant retryable data transfer: Azure Data Factory can overcome rate limits encountered with the source and destination by repeatedly performing the requests and provides ways for the end-user to determine various actions on well-known errors encountered during data transfer pertaining to the type of data at the source.

Azure Data Factory provides a flexible and scalable platform for copying data between different data sources, both within Azure and across other cloud platforms. When the transfer of data is entirely between Azure cloud resources, the Azure integration runtime can be used and the data transfer is extremely fast because it goes over the Microsoft backbone network. The latency is very low for this network.