Systems | Development | Analytics | API | Testing

Key Takeaways from AWS re:Invent 2024

AWS re:Invent is one of my favorite trade shows. It is one of the biggest technology conferences of the year and is an opportunity to have hundreds of conversations with customers and prospects, listen to their priorities and challenges, hopes, and give them a Cloudera tote bag or a pair of orange sunglasses. What follows is a collection of just a few things I learned and observed during my week in Las Vegas.

Integrating Microservices with Confluent Cloud Using Micronaut Framework

Designing microservices using an event-driven approach has several benefits, including improved scalability, easier maintenance, clear separation of concerns, system resilience, and cost savings. With Apache Kafka as an event plane, services now have a durable, scalable, and reliable source of event data. From Kafka topics, a microservice can easily rebuild and restore the state of the data used to serve end users.

Highlights from Confluent AI Day 2024

We hosted our first-ever Confluent AI Day on October 23 in San Francisco and virtually. It was sponsored by Confluent, AWS, and MongoDB, with a vibrant gathering of talent and innovation. With 200 attendees, the full-day event brought together AI developers, technology leaders, and startup innovators to explore how data streaming powers generative AI (GenAI) applications.

Navigating the Future of AI at Yellowfin: Innovation with Care

In this blog, Yellowfin GM Chance Coble discusses the integration of artificial intelligence into our embedded analytics suite, including how we balance innovative features with a responsible approach to the rapidly-evolving fields of AI technologies. At Yellowfin, our philosophy toward artificial intelligence (AI) in business intelligence (BI) solutions is grounded in a deep commitment to innovation and responsibility.

EP 4: Bridging the Gap: Data Professionals, AI, and Real Business Outcomes

Data professionals are at the forefront of today’s digital economy, driving organizational transformation through AI. Yet, despite the vast opportunities AI presents, many data professionals encounter challenges that hinder their ability to lead effectively in this space.