Azure DataParser Offers Cost-Effective SEC Compliant Archiving

17a-4 announces the release of the most cost-effective, fully compliant archiving solution. Azure DataParser is designed to bring many types of data into compliance with minimal cost.

17a-4, LLC, a leader in e-messaging compliance, has released a solution for Azure. Managing electronic compliance records and SQL database back-ups is challenging as both technology and regulatory requirements continue to change. To assist clients with these challenges, 17a-4 has developed an interface between DataParser and Microsoft’s Azure storage which now provides an efficient and cost-effective solution for SEC and FINRA compliance.

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Whether compliance records are retained in a fileshare, SharePoint library or SQL database, the DataParser can pull the compliance content and push it into Microsoft’s Azure Blob storage. This type of storage can run as low as $0.001 per GB per month and comply with either the non-erasable requirements of SEC Rule 17a-4 or with proposed audit trail regulations.

“Often,” says Charles Weeden, Partner, “we find that non-email documents such as G/L, HR .pdf reports or new account applications and trading SQL database records are overlooked during the set-up of an SEC/ FINRA repository. By combining both the DataParser collection engine and Microsoft’s Azure pricing, we are able to offer a solution that offers an extremely competitive price.”

“Currently, many firms are converting to this archiving combination to take advantage of the redundancy and low cost of cloud storage,” continues Mr. Weeden.

DataParser has been designed to automatically collect data from various sources and deliver to a specific Container within an Azure Blob Storage Account. This integration with Azure allows users to easily bring regulated data into Azure Blob storage and take advantage of the WORM/immutable policies offered. DataParser has no impact on the collected data source networks or destination archives. Users’ chat and collaboration activities are not disrupted by the DataParser’s processes.

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