Systems | Development | Analytics | API | Testing

Today more than ever before, businesses must navigate a complex landscape of regulations to ensure they are compliant with various personal data protection laws. From the General Data Protection Regulation (GDPR) in Europe to the California Consumer Privacy Act (CCPA) in the United States, and the Personal Data Protection Law (PDPL) in Saudi Arabia, these regulations set the standards for how businesses collect, store, and process personal data.

Imagine you are developing a streaming application that consumes data from a topic that has a defined schema. You are finally ready to test the application and realize you need a way to produce a sample schematized message. What do you do?

Understanding and monitoring the performance and health of applications and systems is critical. This is where observability comes into play. Observability is about gaining a comprehensive understanding of a system's internal state by analyzing the data it generates within the context of real-time events and actions across the infrastructure.

In today's data-driven business landscape, the ability to predict trends, explain drivers, and act on insights is no longer a luxury—it's a necessity. Yet for many organizations, the path from data to predictive intelligence remains challenging. Data science resources are scarce, and traditional tools often require specialized expertise that most analytics teams lack. At Qlik, we believe that the power of predictive analytics should be accessible to all.

It sounds counterintuitive—using a technology that has trust issues to create more trustworthy data. But smart engineers can put generative AI to work to improve the quality of their data, allowing them to build more accurate and trustworthy AI-powered applications.

Without a doubt, Artificial Intelligence (AI) is revolutionizing businesses, with Australia’s AI spending expected to hit $6.4 billion by 2026. However, according to The State of Enterprise AI and Modern Data Architecture report, while 88% of enterprises adopt AI, many still lack the data infrastructure and team skilling to fully reap its benefits. In fact, over 25% of respondents stated they don’t have the data infrastructure required to effectively power AI.

A prominent global bank was thrust into the spotlight for all the wrong reasons. The institution was hit with a staggering fine – multiple billions – for failing to comply with new data protection regulations that ultimately led to a customer data breach. The breach, which exposed sensitive information, not only resulted in financial penalties but also caused significant reputational damage.