Enterprises have complex IT and technology needs. To reach business goals, organizations must often stitch together a patchwork of software and IT systems. So, it’s understandable that the thought of adding yet another technology—low-code—might cause trepidation. But low-code excels at integrating seamlessly with any technology. Low-code tools speed up development work and enable rapid application development.

This is the third in a series. Read Part 1 and Part 2. “2001: A Space Odyssey” doesn’t spend time on the training contexts of its antagonist, HAL 9000. The only clues we get are upon its “death,” where it regresses back to its earliest lessons, like singing “Daisy Bell” as it winds down for the last time, suggesting it started with the very basics and grew more complex only with time and practice.

For independent software vendors (ISVs), creating unique differentiators and value increasingly entails adopting the latest technologies to enhance your product experience, especially in an ever-evolving competitive landscape with multiple new tech solutions. AI analytics is the latest emerging field in business intelligence (BI) solutions that offers new sophisticated capabilities for the user experience (UX) of your product’s analytics component.

Cybersecurity is one of the most prominent and pressing concerns for businesses today. As developers move more of their web applications to a microservices architecture, data is shared by web service APIs now more than ever. Industry analysts predicted that API attacks would become the most common attack vector by the end of this year. Unfortunately, that prediction has come true.

Metadata governance is the systematic approach to managing metadata, or data about data, to ensure it is accurate, consistently formatted, and securely stored. The main goal of metadata governance is to improve data quality, ensure data privacy, and streamline metadata management. As metadata provides the necessary details about data, such as when it was created, by whom, and its content or purpose, it becomes easier for employees to find, understand, and trust the data they use.

The ability to record and see everything happening across your web applications is essential when building resilient and highly available systems. All of your events—from application logs to errors to user behavior—contain data that could be useful to you and your team. When you have a central place to access all this information, finding issues and their root causes becomes easier because you have the data at your fingertips.

Building a data-driven company starts with having a data analytics strategy. An effective data analytics strategy relies on three key components: people, processes, and data infrastructure. This ensures that your analytics strategy is actionable and accessible to everyone who needs it to make decisions. In this post, we’re sharing 12 tips to help you develop an effective data analytics strategy.

Developing microservices destined to run in Kubernetes presents a unique set of challenges. In this blog post, we’ll explore a new approach leveraging Codezero in order to enhance both productivity and security.

Ever felt overwhelmed by the complexity of the system that you’re testing? Navigating intricate software systems can be daunting, leaving us feeling lost and unsure where to begin. While exploratory testing gives us some degree of freedom to test, we still need some guidance on how to approach those complex systems. This is where heuristics might help by guiding us to efficiently navigate the complexities of software systems and uncover hidden issues.