Press Release: Hush-Hush Announces the Only Data Anonymization Solution to Natively Extend Microsoft

8/22/2017



LAS VEGAS - Aug. 22, 2017 - PRLog -- Hush-Hush, the leading innovator in the data de-identification space, today announced the general availability of its SSIS- based solution release into Azure - the only data anonymization/static data masking solution that natively extends Microsoft's stack of products. With Hush-Hush, enterprise developers can use data masking seamlessly, without the need for any specialized training, and on a pay-as-you-go basis.

"As Microsoft's most recent layoff shows," explains Hush-Hush founder Virginia Mushkatblat, "they see the cloud increasingly growing in importance in the enterprise, meaning less need for direct sales staff selling high-end enterprise licensed software.  But as enterprises realize the significant benefits from moving their software and data to the cloud, many of our clients told us they need better solutions to secure that data. That's why we built Hush-Hush.  It is the only such data masking solution that is seamlessly integrated into Microsoft's Azure cloud platform."

This solution is much easier to use, and more cost-conscious than other data security solutions. First, no training is required, since users utilize the familiar SSIS components add-on pack which implements prepackaged algorithms which are versatile and easy to reuse. Second, developers also have the cost benefit of only paying for what they use, and not having to purchase a license for a separate data security tool.  These two benefits mean that any size organization can now easily and affordably stay compliant.

Enterprise-Wide Data Management for Azure

The Hush-Hush data masking solution is innovative, versatile, and cost-effective. It can mask data in most RDBM such as SQL Server, Oracle, IBM DB2, Teradata,MySQL, PostgreSQL and others, files, and Big Data solutions. It effectively resolves the development time-to-market challenge that a lot of organizations face: how to de-identify data quickly prior to development, and do that cost-consciously, so that an organization of any size could afford to stay compliant – a luxury now de-facto afforded only by bigger companies.

Hush-Hush also eases the burden of having to keep developers trained on yet another tool.  Since the familiar SSIS components add-on pack implements prepackaged algorithms, users do not have to do any additional training to use Hush-Hush. The various algorithms allow for a multitude of solutions, and useful examples of masking flows come with the Virtual Machine – they are easy to reuse. Existing ETL processes can also be reused by augmenting already-written SSIS packages with masking algorithms, or reusing the packages with masking algorithms in production by turning the Pass-through feature on.

The tool is truly an enterprise-wide data management solution, as it allows for both explicit and implicit referential integrity across a variety of sources, centralized management with the SSIS deployment model, as well as logging and auditing capability. It is also a good enterprise-wide choice for DevOps as it allows a complete integration into the development lifecycle using already existing infrastructure, and integrating data masking into their existing ETL processes.

Hush-Hush was the very first solution that allowed enterprises to move their development into the cloud securely via SSIS – and now, recognized by the Microsoft Azure team, it continues to protect development on-premises and in the cloud with the added convenience of the Hush-Hush Data Masking Azure Virtual Machine.

To do a trial of the solution, please visit Hush-Hush Azure solution at https://azuremarketplace.microsoft.com/en-gb/marketplace/apps/hush-hush.Hush-Hush-ssis-data-masking-sql2012-standard?tab=Overview

To learn more, please visit this.

About Hush-Hush

Hush-Hush is an offspring of Firm Solutions, Inc., providing enterprise consulting solutions for fourteen years. While working on solutions in the financial industry, it became clear there was an unmet need in the market for easy-to-use data de-identification solutions and Hush-Hush was born.


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