Half of C-suite want to 'completely overhaul' how they use data
2025 will see UK businesses undertake a major shake up of their IT and data practices, new research shows.
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Modern Software Development For Today's Systems & Applications
What Made Current 2024 Unforgettable? Hear From Our Attendees | Current 2024
In this recap video from Current 2024, attendees share their favorite moments from the event. From insightful talks on data streaming innovation to hands-on workshops and networking opportunities, hear what participants found most valuable.
Windowing with Table-Valued Functions | Apache Flink SQL
Apache Flink SQL makes it easy to implement analytics that summarize important attributes of real-time data streams. There are four different types of time-based windows in Flink SQL: tumbling, hopping, cumulating, and session. Learn how these various window types behave, and how to work with the table-valued functions that are at the heart of Flink SQL’s support for windowing.
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.
SQL for data exploration in a multi-Kafka world
Every enterprise is modernizing their business systems and applications to respond to real-time data. Within the next few years, we predict that most of an enterprise's data products will be built using a streaming fabric – a rich tapestry of real-time data, abstracted from the infrastructure it runs on. This streaming fabric spans not just one Apache Kafka cluster, but dozens, hundreds, maybe even thousands of them.
How Confluent Fuels Gen AI Chat Models with Real-Time Data
Discover how GEP, an AI-powered procurement company, utilized Confluent's data streaming platform to transform its generative AI capabilities. Integrating real-time data into their AI models enabled GEP to provide a contextual chat-based service. This chatbot allowed GEP customers to build their own tools simply by communicating in English with a chatbot.
Why Real-Time Data is Crucial to Developing Generative AI Models
Learn how GEP, an AI-powered supply chain and procurement company, harnesses real-time data streaming through Confluent Cloud to fuel its generative AI solutions. With seamless integration into Azure OpenAI services and GPT models, GEP’s generative AI chatbot delivers document summaries and risk management insights to its customers.
Preparing the Consumer Fetch: Kafka Producer and Consumer Internals, Part 3
Welcome back to the third installment of our blog series where we’re diving into the beautiful black box that is Apache Kafka to better understand how we interact with the cluster through producer and consumer clients. Earlier in the series, we took a look at the Kafka producer to see how the client works before following a produce request as it’s processed by the cluster.
Replication in Apache Kafka Explained | Monitoring & Troubleshooting Data Streaming Applications
Learn how replication works in Apache Kafka. Deep dive into its critical aspects, including: Whether you're a systems architect, developer, or just curious about Kafka, this video provides valuable insights and hands-on examples. Don't forget to check out our GitHub repo to get all of the code used in the demo, and to contribute your own enhancements.
Quick Thinking: 86% of UK business leaders must make decisions "faster than ever before"
As the speed of decisions increases, new Confluent research shows half of C-level executives are relying on 'gut feel' due to a lack of real-time data.