Insurance companies have long relied on data to assess risk, underwrite policies, and handle claims. However, as the volume of data grows, so does the need for sophisticated tools to turn that information into actionable insights. Simply having access to data is no longer enough. To succeed, insurers must be able to harness the power of their data—transforming it into a strategic asset that drives both operational efficiency and improved customer outcomes.

Have you ever wanted to make sure your assumptions about your code are correct? That’s where assertions come in. In programming, an assertion is a simple way to verify that certain conditions hold true in your code, helping you catch potential errors early before they snowball into bigger problems. Imagine building a house—you wouldn’t start putting up walls without first making sure the foundation is solid, right? Assertions work the same way in your code.

IoT technologies are poised to transform traditional insurance business models, from how insurers engage with customers to the core risk assessment and management processes. In today’s hyperconnected world, the sheer volume of data available for risk pricing is growing unprecedentedly. With the proliferation of sensor-based smartphones, wearables, and smart home devices, the expanding IoT landscape offers insurers numerous business opportunities.

Yellowfin 9.13 is a significant release that introduces a number of security updates, quality improvements and product enhancements, as requested by our customers. In this blog, we will cover some of the biggest highlights in the 9.13 release. For the full list of updates, please visit our release notes page.

With generative AI, you have the opportunity to deliver a data strategy that helps business people answer their most pressing data questions—providing unprecedented value to your internal teams, partners, and customers. Hype around GenAI has overwhelmed people with too many use cases and too little focus on achievable value. That’s why we sponsored a first-of-its-kind survey with MIT SMR Connections, asking 1k global data and business leaders questions.

Application programming interfaces (APIs) power countless applications and services in today’s world. However, the complexity and scale of modern API ecosystems often create a blind spot for developers and operations teams. API monitoring can solve a lot of these challenges. In this article, we discuss some core concepts and the benefits of API monitoring, along with key API metrics you should track.

Imagine a world where your sensitive data moves effortlessly between clouds – secure, private, and far from the prying eyes of the public internet. Today, we’re making that world a reality with the launch of Cloudera Private Link Network. Organizations are continuously seeking ways to enhance their data security. One of the challenges is ensuring that data remains protected as it traverses different cloud environments.

As applications increasingly rely on APIs to drive critical functionalities, the demand for high-performance, scalable, and secure API management solutions has never been greater. DreamFactory, an on-premise API generation and management platform, is designed to meet these needs by providing robust features such as rate limiting, caching, SQL function integration, and multi-tier architecture.

We begin with a very brief overview on the underpinnings of quantum computing and the notion of quantum algorithms. Next we show the threats on today’s cryptographic protocols that originate from quantum algorithms.

Java is one of the most popular programming languages, known for its portability, scalability, and rich ecosystem. One of the critical components of the Java Runtime Environment (JRE) is the heap space, which plays a crucial role in memory management. While Java’s automatic memory management via garbage collection is powerful, it is not immune to problems. One such problem that developers frequently encounter is the dreaded OutOfMemoryError: Java heap space.