Systems | Development | Analytics | API | Testing

In the age of AI, the hunger for fresh, reliable data to power machine learning (ML) models and real-time analytics is insatiable. Yet, organizations frequently hit roadblocks when trying to bridge their operational data in motion, typically flowing through Apache Kafka, with their data at rest in data lakehouses. On one side, you have the data streaming platform, the central nervous system managing the real-time flow of business events.

Most companies believe they own their customer data. Most are wrong. Data is your most powerful asset for fueling decisions, improving customer experiences, and providing a competitive edge. But if your customer, marketing, or product teams rely on third-party analytics tools, there’s a great chance you don’t actually own your data. It’s processed, stored, and sometimes even monetized by vendors who decide your access and control levels.

The information in this blog post is based on a real-life scenario shared by a user on our Katalon Community forum and is intended to inspire peer-to-peer discussion and collaboration. Please always test solutions thoroughly before implementing them in a production environment. Feel free to continue the discussion here.

Want to speed up AI projects? DreamFactory's RBAC-secured APIs reduce development time by 85% while ensuring top-level security. Here's how.

In today’s software landscape, APIs are more than just a technical interface, they’re the connective tissue of modern digital products. Organizations embracing API-first strategies aren’t just producing better APIs – they’re fueling faster innovation, scalable architectures, and smoother collaboration across teams. But transitioning to an API-first strategy isn’t always a smooth ride.

Mobile apps aren’t just another digital touchpoint anymore – they’re the front line. Whether you’re banking, booking a ride, ordering dinner, or catching up on emails, it’s happening on your phone. But when things go wrong, customers don’t wait around. According to PwC, 32% of customers would stop doing business with a brand they love after just one bad experience.

We are proud to announce a new integration between MLRun, the open-source AI orchestration framework, and NVIDIA NeMo microservices, by extending NVIDIA Data Flywheel Blueprint. This integration streamlines training, evaluation, fine-tuning and monitoring of AI models at scale, ensuring high-performance, low latency and lowering costs while significantly reducing the manual effort required through intelligent automation.

Google Cloud Serverless for Apache Spark, now available in BigQuery is an open-source, zero-ops, high performance, and unified analytics platform.

Relational databases rely on SQL, or Structured Query Language, as the standard way to control and interact with their stored data. In the Node.js ecosystem, Sequelize is a prominent Object-Relational Mapping(ORM) library that bridges the gap between Node.js apps and SQL databases, enabling you to interact with your data using familiar JavaScript idioms. This article will guide you through using Sequelize to connect to databases, run queries, and handle results within your Node.js projects.

Anyone who has tried to build a recommendation engine or a churn predictor knows the moment the excitement fades. The prototype looks good in the notebook, but the training data contains typos, half-missing properties, and events that somehow morphed between different devices. The model stumbles, engineers lose faith, and everyone wonders where all that AI magic went.