The dynamic landscape of product development continuously increases the scope of what is demanded from quality engineering (QE) professionals. So, it is not surprising that workplace learning and upskilling are critical to the organizational success, as highlighted by Workplace Learning Report: Without a doubt, the more technical side of the skill spectrum - e.g.

Complexity is increasing exponentially. Compared to just 20 years ago, our personal lives and the way organizations do business has changed completely. This translates into increasingly complex and interrelated business processes and a sprawl of IT systems that can only function when each of its components runs flawlessly. Navigating this business/IT complexity can only be overcome by combining business process solutions, quality assurance tools and human ingenuity and expertise.

For iPhone and iPad app development, one of the main aspects is the app’s performance. Performance is about your application not crashing, but also how quickly and smoothly it can carry out its functions when users interact with it. An application whose functions consume a lot of battery life, or an application that doesn’t like to wait too long until it finishes whatever it wants to do, can lead to users uninstalling the app.

The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.

Every QA tester knows: time is money. When something breaks down on your website or web application, it can cause major issues for users within minutes. Because you’re constantly working to prevent fires from spreading (or happening at all), it’s important to have numerous strategies at the ready to help you manage your time wisely. One of these QA testing timesavers is called smoke testing. But exactly what is smoke testing?

Generative AI in manufacturing refers to using advanced AI algorithms and generative models to optimize various aspects of the production process. This technology enables manufacturers to create innovative product designs, streamline workflows, predict maintenance needs, and boost efficiency in frontline operations. By integrating generative AI, manufacturers can enhance decision-making, collaboration, and data insights, ultimately improving overall performance.

A partnership between Google Cloud and Gretel lets data engineers generate synthetic data within BigQuery.

BigQuery’s pipe syntax introduces an intuitive, top-down syntax for understanding data transformations, and is used in Cloud Logging Log Analytics.