Systems | Development | Analytics | API | Testing

Accelerate data movement into the Databricks Data Intelligence Platform to execute analytic workloads, AI and GenAI.

There is a growing recognition that insurers can introduce data, analytics and AI into virtually all of the important insurance functions and workflows, including product development, pricing and risk selection, underwriting, claims management, contact center optimization, distribution management, reinsurance, and understanding and shaping customer journeys. Here are some of the exciting ways insurance companies can put data to work.

These days, where web professionals juggle multiple projects and tight deadlines, efficiency isn’t just a goal—it’s a necessity. Geekbot emerges as a beacon of productivity for teams using Slack and Microsoft Teams. With years of industry experience, many have seen tools come and go, but Geekbot stands out for its ability to keep teams engaged, projects on track, and communication seamless, ultimately boosting overall team morale and performance.

We all know the why it’s important to write clean, reliable code. But let’s face it, catching bugs before they wreak havoc on our applications can feel like chasing after a greased weasel. That’s where testing frameworks come in, acting as our trusty bug-hunting companions. In this blog, we’ll be putting two popular frameworks – Jasmine and Mocha – head-to-head.

Now-a-days the data needs to be shared across different systems and platforms. One of the most common formats for this data exchange is JSON (JavaScript Object Notation). Understanding how to properly handle special characters in JSON is crucial for ensuring data integrity. In this blog, we’ll explore JSON escape and unescape, explain their importance. So let’s get started!

As can be inferred from their name, foundation models are the foundation upon which developers build AI applications for tasks like language translation, text summarization, sentiment analysis and more. Models such as OpenAI's GPT, Google's Gemini, Meta’s Llama and Anthropic’s Claude, are pre-trained on vast amounts of text data and have the capability to understand and generate human-like language.