The end users of disguised data—the testers—in a test data privacy project typically have two objections to how pseudonymization affects test data quality. The first objection is easily handled, but the other must be delicately approached with the right solution.
When our journey towards mitigating the mainframe skills shortage at our company began, we responded to the foreshadowing of a major skills gap that needed our immediate attention; we realized the next generation of developers wasn’t going to come to us, and that we needed to go to them; and we created a plan for how we should begin reaching out to them.
IMS is still used by some of the largest and most important mainframe customers in the world. It still has the ability to be incredibly fast and efficient. But developers often forego measuring IMS transaction performance, a critical component to developing and delivering mainframe software in a digital economy that expects speed and quality.
Test environments are vulnerable against GDPR legislation, and therefore, action must be taken to desensitize test data and improve data protection. More than likely, a lot of IT organizations need to be thinking of how to start a test data privacy project.
Once people commit to change and work through the process of detaching from old constraints, with patience the benefits of Agile will unfurl for an organization.
A word of advice: I’d make sure you have feedback between customers and development, development and operations, QA and customers, and QA and development. Having multiple feedback loops circling between these groups will yield some amazing results, enabling your mainframe shop to develop and deliver software at a remarkable pace.
As technologies of engagement flourish and access mainframe data millions of times daily, companies are reversing their neglect of the mainframe and working hard to reinstitute the talent and knowledge needed to leverage the platform as the backbone of their success.
The EU General Data Protection Regulation legislation has been published in the Official Journal, making it a valid law in all 28 EU countries, and it’s coming into full force two years from today on May 25, 2018.
For a perspective of how Compuware goes about finding Millennial mainframe talent, I spoke with Leigh Ann Ulrey, responsible for Compuware’s Global Talent Acquisition. Ulrey is the first and last touchpoint for candidates in Compuware’s recruitment process, giving her a unique vantage point of the generational changeover between retiring mainframe experts and Millennial developers.
While I value my history doing data analysis with green screens and whiteboards, I’m relieved this method is fading away like the Bubblegum pop stars of the 70s. Clear data visualization of data relationships provides much greater value to mainframe shops looking for ways to innovate for the fast-paced digital economy.
When I see someone staring at a green screen and coding, I get the same sense as when I watch a historical reenactment: a strong sense of how things were. Nostalgia is fine, but that doesn't mean we should continue living in the past.
Until recently, data controllers maintained sole responsibility for upholding EU data protection laws, and made sure data processors they partnered with followed suit. However, under the EU’s newly adopted GDPR, data processors will no longer be free of liability for breaking data privacy laws, and will share with data controllers the onus of data protection for EU citizens.
“I’ve never had any vendor on any platform respond to my input so quickly with a tool that so fully met my stated need,” says Mike Wells. “Compuware’s ability and willingness to support Ameritas’ cross-platform Agile strategy is proof-positive that the mainframe can be an integral and highly adaptive element in any company’s digital business strategy—if you have the right vision and take the right actions.”
At first, the juxtaposition of mainframe and Eclipse seems counterintuitive—different syntaxes, different cultures, different generations. But the introduction of Java to the mainframe is blurring the line between developers who represent these differences.
Most IT teams use a lengthy process that hides broken builds and software integration issues until the end of a release cycle. By then, identifying people responsible for breaks and diagnosing their missteps is an exhausting chore. A process of continuous builds will help your team more quickly identify the origins of broken software.
There’s a longstanding feud between mainframe application development and open systems development teams. Mainframe dev believes slow and steady keeps the company secure, while open systems dev follows a DevOps approach, celebrating innovation, agility and speed.
The GDPR is making data protection more complex for companies. The coding of data masking rules for each and every column (field) is a redundant task. Data Elements solves this problem by reducing the complexity and tedium involved.
As a Product Manager I’m constantly looking for the win-win option of something that provides flexibility with minimal complexity. Often this balance is only achieved by starting with the right philosophy and continually learning from customer experience.
Mainframe shops need Agile processes like the 2-week COBOL sprint to more quickly develop and deliver software for customers in the digital economy. To carry this out, you build a scrum team comprised of people across functional areas committed to daily interaction.
Recently, the EU Parliament adopted the General Data Protection Regulation (GDPR) legislation. Apart from losing credibility, companies failing to comply with the GDPR will face fines up to €20 million or 4 percent of annual worldwide turnover—whichever is greater.