Systems | Development | Analytics | API | Testing

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Databricks + Unravel: Achieve Speed and Scale on the Lakehouse

Companies are under pressure to deliver faster innovation, enabled by cloud-based data analytics and AI. In order to deliver faster business value, data teams are looking to achieve speed and scale through data and AI pipeline performance and efficiency. A recent MIT Technology Review Insights report finds that 72% of technology leaders agree that data challenges are the most likely factor to jeopardize AI/ML goals.

Fail Fast, Build Better

Is it better to launch fast or wait for perfection? @Saurabh Shanbhag explains the "fail fast" strategy, where teams quickly release imperfect products to get real customer feedback and improve. Instead of taking years to perfect, they launch in months, see what works, and adjust from there. This approach helps companies adapt, find market fit, and build better products based on actual user insights.

How Thrivent Uses Real-Time Data for AI-Driven Fraud Detection

In today’s fast-paced financial services landscape, customers have a shorter attention span than ever. To meet clients’ growing demands for real-time access to information and keep innovating in areas like fraud detection and personalized financial advice, Thrivent needed to overhaul its data infrastructure. With data scattered across siloed legacy systems, diverse tech stacks, and multiple cloud environments, the challenge was a bit daunting. But by adopting Confluent Cloud, Thrivent was able to unify its disparate data systems into a single source of truth.

Your Guide to SAP Testing Automation & How to Get Started

For enterprises relying on SAP systems, ensuring smooth operation through updates, integrations, and daily operations is crucial. Manual testing of these complex systems increases time to market and the likelihood of human error. The solution? SAP testing automation, which enables faster, more reliable testing, ensuring your business-critical processes run smoothly without bottlenecks.

Test Case Design Techniques: The Definitive Guide

The first step is often the hardest, and in software testing, this is especially true. When presented with a system, how do you go about and decide what to test? Standing in the middle of the unknown, we need guidance, and learning about test case design techniques is a good place to start. In this article, we’ll show you: Let’s dive in!

AI's Impact on Human Intelligence: Are We Getting Smarter or More Dependent?

Artificial Intelligence (AI) has become an inseparable part of our lives, revolutionizing industries, transforming workspaces, and influencing how we interact with technology. From virtual assistants like Siri and Alexa to advanced machine learning algorithms driving breakthroughs in medicine, AI is everywhere. But as AI continues to evolve, a growing question lingers: Is AI making us smarter or more dependent?

Are Self-Driving Cars Safe?

Are self-driving cars safe? The software in modern cars contains more than 100 million lines of code that enable many different features — cruise control, speed assistance, and parking cameras. And, the code within these embedded systems only gets more complex. This trend will continue as cars of the future become more connected. Cars are increasingly dependent on technology. And they will progressively become more autonomous — and ultimately self-driving.

The ultimate guide to Sidekiq scheduled jobs

Sidekiq is one of the most popular open-source background job libraries for Ruby. As one of ActiveJob's most popular backends, it's often used to run asynchronous jobs in Rails applications. It leans on Redis to manage queues and jobs, which makes it fast. Developers can run background jobs using Sidekiq with or without ActiveJob, and we'll explore both in this article. Just as useful - Sidekiq scheduled jobs allow you to run a job after a given amount of time or at a given time.