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Janardhan (@janardhan)
6 months ago

With over 1 million members and assets of over $17 billion, Boeing Employees' Credit Union (BECU) is the largest credit union in Washington and the fourth largest in the United States. With more than 40 cashless branches and only a few traditional locations, BECU is a digitally focused institution.


[BECU Online Banking](<https://techprodata.com/becu-online-banking-login/ >) continually endeavors to make banking simpler, more advantageous, and secure for its individuals. That means quickly implementing enhancements to the online banking systems of BECU without interfering with services or jeopardizing security. A key test looked by BECU was building a lithe testing foundation while maintaining the most elevated information protection and security principles.

BECU required a safe DataOps solution that satisfied these particular needs:

sensitive data collection. BECU required a solution that could automate the process of consistently masking sensitive data values and identify sensitive data values across all of its environments.

Consistency and repeatability of the mask. Applications needed to be masked in the same way every time and work with both masked and unmasked data in the same way. The arrangement is additionally expected to keep up with referential honesty across concealed-level records and information bases.

templates for masking that come pre-made. The BECU team needed a straightforward solution with predetermined rules that the business could immediately use.

the number of databases and flat files that are supported. BECU required a solution that could cover up Oracle, SQL Server, and more than one hundred flat files in all nine important applications, such as CRM, loan originations, and member portal systems.

masked data auditing and reporting In order to ensure that masked environments were not contaminated with unmasked confidential data, the credit union required a method for tracking masked data across different sources over time.

Solution BECU selected the Delphix Data Platform for masking data in its new testing infrastructure after evaluating three different vendors because:

Even when data changes over time, Delphix consistently masks data across relational database platforms and flat files. Masked data is also protected by Delphix's referential integrity across databases and files.

The first crucial step in protecting sensitive data is addressed by Delphix: finding where the gamble lies by giving builtin information profiling.

Custom masking rules can be created using Delphix's pre-built masking functionality without the need for any programming or administrative expertise.

Delphix supports a wide range of heterogeneous databases, including Oracle, SQL server, DB2, and file systems, and it is platform-independent.

Teams must repeat the entire manual process of extracting, moving, and importing data to the cloud using legacy AWS data refresh methods. Delphix, on the other hand, continuously collects data from production sources, so BECU can keep their on-premise and cloud environments in sync with a hybrid cloud architecture.

After that, their data is masked and transferred to AWS. BECU is able to quickly and easily deliver new virtual data copies to a team of over 200 developers with the help of secure, fresh data that is available in the cloud.

Results With Delphix, BECU was able to surpass its target for data masking, bolstering the company's stringent security measures:

BECU met the initial requirement that masking not take longer than 24 hours by masking 662 tables, 3,507 columns, and 680 million rows of data in 15 hours.

They met compliance requirements ahead of schedule and completed the implementation process in six weeks. The team estimated that installing and beginning to mask data with competitors' tools would have taken 18 to 24 weeks.

BECU was able to proceed with minimal support because Delphix specialists collaborated with team members to build the foundation of a masking Center of Excellence.

BECU is also able to deploy products up to twice as quickly by making use of the virtualization capabilities of the Delphix Data Platform to speed up the distribution of masked data and save time and effort overall.