The journey from manual testing to test automation can be daunting, with several potential roadblocks limiting success. Some factors that make this transition challenging include the high upfront costs, limited access to talent, and the need to implement sustainable script maintenance. These factors can be overwhelming and seem at odds with the objective of leveraging automation, which is to relieve pressure from product executives to increase software release velocity, improve efficiency, and cut costs.

Generating files for data extracts, reporting and even data migration is a crucial part of any back-end team. A typical data team will have to generate many files to be sent to various clients or consumers inside or outside of the organisation. As with all things, the question is how can the generation of those files be made simpler, and can it be automated to such a degree that files are dynamically generated? The short answer is yes, it can be done dynamically.

Since semiconductor design comes with complex challenges and high stakes – including strict regulations, tight time-to-market timelines, and an immense cost of error – teams need strong, trusted design tools. These teams turn to electronic design automation (EDA) software to streamline and automate chip design, predict certain elements of the design process, and test their technology as they develop it.

Automating a process can be complex, especially when it’s a long-running process with many steps and complex business rules, cross-cutting multiple departments and systems in an enterprise. To automate a process like this from end to end, you’ll need a process automation strategy and software. Assuming you’ve ticked both of those boxes, the next step is putting those things to work, which is the focus of this post.

We've all been involved in automated processes in companies, governments, or schools that might have made sense in theory—but fell apart when they were rolled out. That’s because automating a process is different from automating a process well. Developing a process automation strategy helps you automate effectively—but only if it includes these three often-overlooked elements.

It's about that time again! Time to talk about the elephant in the testing room: QA Automation. Well, it's not just a fancy buzzword anymore; it's a game-changer in the world of automation testing services. Imagine a world where swift and tireless scripts replace all the repetitive and mundane testing tasks, catching bugs before they even dare to show up. Sounds impressive, right? That is precisely what QA automation testing services help you with.

For decades, the sci-fi dream of simply speaking to your device and having it perform tasks for you seemed far-fetched. In the realm of test automation and quality assurance, this dream is inching closer to reality. With the evolution of generative AI, we’re prompted to explore what’s truly feasible. Embedding AI into your quality engineering processes becomes imperative as IT infrastructures become increasingly complex and integrated, spanning multiple applications across business processes.

When compared with web testing or mobile testing, desktop testing has relatively lower demand. The widespread adoption of web and mobile applications as well as the increasing reliance on online services is the reason why. However, for businesses where desktop applications are still in use, having a decent tool for this activity is a must. In this article, we list down the top 10 desktop automation tools for you to choose from.

Ready or not, AI workflow automation is poised to transform business operations from the shop floor to the C-suite in the AI economy. The situation is a byproduct of the generative AI boom. And yet, so many companies have hardly scratched the surface of AI automation’s full potential in their business operations. The more these companies get AI workflow automation to work for them, the more agility, efficiency, productivity, and economies of scale they’ll get back for themselves.