Systems | Development | Analytics | API | Testing

Engineering data management is a key skill for data analysts who handle complex datasets across engineering systems. This field involves processes for managing, organizing, and optimizing data generated by engineering teams, such as IoT device data, operational metrics, and manufacturing details.

Learn how CHS Inc., Pitney Bowes and Envision Pharma use Fivetran for high-volume database replication to streamline operations, drive growth and save money.

Enjoy a love letter to Selenium from a veteran Saucer.

The world of quality assurance (QA) has changed, and there’s no turning back. Digital transformation is driving the need to produce high-quality software faster, while also keeping costs under control. The old idea of choosing between speed, cost-efficiency, or quality? That’s out the window. Today, you need all three to succeed, and they’ve got to work together.

AI is no longer just a buzzword – it’s the driving force behind the next wave of innovation in the software industry. Companies that embrace AI today are automating tasks, boosting efficiency, and unlocking new levels of productivity. However, as revolutionary as AI is, adopting it within technical software teams isn’t without its challenges. From skill shortages to navigating ethical dilemmas, businesses face a steep adoption curve.

Developer Experience (DevEx) is a general term that encompasses all of the interactions a developer has with their work environment. The tools that a developer uses, the processes they employ, and even the organizational culture, all play a role in establishing a great Developer Experience – or, unfortunately, a bad one.

If you're worried about the potential for heightened regulatory scrutiny in financial services, you're not alone. Business operations teams everywhere are focused on the end-to-end, client lifecycle management (CLM) process as they cope with ever-changing regulations governing how, when, and where client data can be stored and accessed. It's hard to stay compliant when customer data is spread across multiple operational silos.

The process of preparing and submitting labeling to regulatory authorities can be time-consuming and complex, requiring specialists’ input and careful coordination across organizations and functions to ensure the quality and safety of products going to market. This often causes delays that ripple across the supply chain, impacting profitability and patient care.

Phoenix and Elixir are designed at their core to build real-time, fault-tolerant applications. With its elegant syntax and the robustness of the Erlang VM, Elixir is an ideal candidate for tackling the challenges of distributed state management. This two-part series will guide Phoenix/Elixir developers through the intricacies of working with Phoenix in a distributed setup.

Combining Artificial Intelligence and human intelligence in testing becameessential for delivering high-quality products quickly and efficiently. AI excels at automating repetitive tasks, analyzing vast datasets, and improving test coverage. Humans, on the other hand, bring creativity, critical thinking, and the ability to handle complex scenarios that machines can’t easily navigate. Together, they form a powerful synergy that enhances speed and accuracy in testing but also brings challenges..