Data analytics is the science of analyzing raw data to draw conclusions about it. The process involves examining extensive data sets to uncover hidden patterns, correlations, and other insights. With today’s technology, data analytics can go beyond traditional analysis, incorporating artificial intelligence (AI) and machine learning (ML) algorithms that help process information faster than manual methods.

Many people don’t test their WordPress websites, and it’s a problem. While the core of WordPress is fairly well-tested by its creators, users, and the open-source community, the same cannot be said for every plugin and theme. There’s an infinite combination of versions, hosting environments, plugins, themes, and configurations. You can’t trust the community to catch every bug that could affect your website.

In today’s market, the power of a cohesive brand identity cannot be overstated. However, manually configuring consistent branding themes across multiple platforms can be a tedious process. That’s where Asgardeo’s new AI Branding feature comes in, offering a smarter way to align your digital identity in Asgardeo with your own brand.

More easily manage AI spend, build AI agents and chatbots, get real-time AI responses, and ensure content safety We're introducing several new Kong AI Gateway capabilities in Kong Gateway 3.7 and Kong Gateway Enterprise 3.7, including enterprise-only and OSS improvements. Read on for a full rundown of the new AI-focused features.

The dual-write problem occurs when two external systems must be updated in an atomic fashion. A classic example is updating an application’s database while pushing an event into a messaging system like Apache Kafka. If the database update succeeds but the write to Kafka fails, the system ends up in an inconsistent state. However, the dual-write problem isn’t unique to event-driven systems or Kafka. It occurs in many situations involving different technologies and architectures.

The generative AI industry is changing fast. New models and technologies (Hello GPT-4o) are emerging regularly, each more advanced than the last. This rapid development cycle means that what was cutting-edge a year ago might now be considered outdated. The rate of change demands a culture of continuous learning and technological adaptation.