One of the benefits of Ruby's developer-friendly syntax is that it's straightforward to quickly build scripts to automate tasks. Web scraping with Ruby is fun, useful, and straightforward. In this article, we'll explore using HTTParty to pull a web page and check it for a given string. To be specific, we'll build a cron job in Ruby to check if a product is in stock on a website!

For insurance companies, balancing customer expectations with the rigorous requirements necessary to mitigate risks poses a challenge. Especially when you’re using manual underwriting processes. By turning to artificial intelligence (AI) in insurance underwriting, you avoid costly delays, streamline your employees’ processes, improve accuracy, and create an optimal customer experience. In this blog post, you’ll learn how AI facilitates greater efficiency in underwriting.

Over the past year, we’ve been dedicated to making Databox faster and more powerful for you and your team. We’ve introduced new features, visualizations, and integrations to help you leverage your data to make better decisions. In case you missed any of these updates, we’ve put together a roundup of the top highlights from 2024.

Privacy is no longer a growing requirement for doing business — it's the new status quo. The stakes for not protecting it have only intensified. Consumers have been demanding greater control and privacy over their data for years, and now vast numbers are taking action to protect it, turning off tracking, using cookieless environments and relying on ad blockers at rapidly increasing rates.

Businesses face an ever-growing challenge: how to protect and manage their most valuable asset – their data. As organizations scale and digital transformation accelerates, the volume generated daily is staggering. IDC predicts that the global datasphere will grow to 175 zettabytes by 2025, requiring a substantial increase in storage capacity across the industry.

Heuristics is the key to turn you into the Turkish Olympic guy. It is something that comes with experience. At a certain point, experts all develop that “sense” in their field of work. Repeated exposure to hundreds of problems helps them recognize patterns that beginners don’t easily see. Heuristics is not always foolproof, but it's good for immediate problem-solving.

Data pipeline automation plays a central role in integrating and delivering data across systems. The architecture is excellent at handling repetitive, structured tasks, such as extracting, transforming, and loading data in a steady, predictable environment, because the pipelines are built around fixed rules and predefined processes. So, they will continue to work if you maintain the status quo, i.e., as long as your data follows a consistent structure.

Before we dive in, we want to remind our readers that the Konnect engineering team actively uses Kong products like Kong Gateway, Kong Mesh, and Insomnia. In this post, we'll showcase the power of Kong Gateway and two plugins — the JQ and Request Transformer Advanced Plugins — to govern and configure APIs, and explain how it played, and continues to play, a crucial role in the release of a new v2 Konnect API specification. The key takeaway here is: don’t do more work than is necessary.