Compuware divvies up ‘diverse’ data, for DevOps

Diversity matters, in all walks of life, obviously.

Data diversity is also an issue because data comes in many ‘types’, that is – structured, unstructured, semi-structured, big, dark, geo-tagged, time-stamped and so on.

Aiming to define, distill, divvy up and deliver a route through all these types of data diversity for DevOps teams this month is Compuware with its Topaz for Enterprise Data product.

The product provides data visualisation, extract and load and advanced data masking capabilities.

NOTE: Data masking is a method of creating a structurally similar but inauthentic version of an organization’s data that can be used for purposes such as software testing and user training. The purpose is to protect the actual data while having a functional substitute for occasions when the real data is not required.

Have you got PII?

Compuware says that data masking is a top concern today, given the importance of protecting personally identifiable information (PII) and complying with regulatory mandates.

CEO Chris O’Malley argues that Topaz for Enterprise Data can be used by enterprises with large diverse datasets of high business value residing on the mainframe that contain sensitive business or personal information.

“As senior mainframe professionals retire, large enterprises must transfer responsibility for stewardship of this data to a new generation of DevOps artisans with less hands-on mainframe experience,” he said.

Topaz for Enterprise Data allows DevOps users to understand relationships between data even when they lack direct familiarity with specific data types or applications, to ensure data integrity and resulting code quality. It can also convert file types as required.

Topaz users can access all these capabilities from within a Eclipse development environment.

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