Connecting multiple systems and exchanging data among them is afrequent requirement in many business scenarios. This typically involves one or many source systems, an intermediary processor, and one or many destination systems. Some organizations invest in purpose-built solution suites such as Data Warehouse, Master Data Management (MDM), or Extract, Transform, Load (ETL) platforms, which, in-theory, cover a wider spectrum of requirements.

Application programming interface (API) automation testing is a type of automated testing that focuses on the performance and functionality of APIs. This process can test APIs for correctness, compatibility, and efficiency. API automation testing can ensure that APIs function properly and meet consumers’ expectations. Here’s the key things to know about API automation testing: Table of Contents.

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.