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The Confluent Q1 '24 Launch

The Confluent Q1 ’24 Launch is packed with new features that enable customers to build, connect, and consume intelligent data pipelines seamlessly and securely Our quarterly launches provide a single resource to learn about the accelerating number of new features we’re bringing to Confluent Cloud, our cloud-native data streaming platform.

Confluent Cloud for Apache Flink | Simple, Serverless Stream Processing

Stream processing plays a critical role in the infrastructure stack for data streaming. Developers can use it to filter, join, aggregate, and transform their data streams on the fly to power real-time applications and streaming data pipelines. Among stream processing frameworks, Apache Flink has emerged as the de facto standard because of its performance and rich feature set. However, self-managing Flink (like self-managing other open source tools like Kafka) can be challenging due to its operational complexity, steep learning curve, and high costs for in-house support.

AI in Banking: 5 Impacts Artificial Intelligence Will Have on the Industry by 2025

The potential impact of AI in banking appears boundless. A 2023 McKinsey report found that effectively incorporating generative AI tools into business operations could lead to annual operational savings ranging from $200 billion to $340 billion for the global financial services industry. These cutting-edge technologies can also enhance customer satisfaction, attract more potential customers, and improve employee experience.

Why a Solid Data Foundation Is the Key to Successful Gen AI

Think back just a few years ago when most enterprises were either planning or just getting started on their cloud journeys. The pandemic hit and, virtually overnight, the need to radically change ways of working pushed those cloud journeys into overdrive. Cost-effective adaptability was essential. And the companies that could scale up or scale down quickly were the ones that navigated the pandemic successfully. Migrating to the cloud made that possible.

Top 4 Programming Languages for IoT Development

IoT startups serve various purposes such as increased performance, security, comfort, and entertainment. However, implementing IoT projects requires a mix of skills, knowledge, and technologies, including hardware, software, cloud computing, networking, and analytics. Of course, a key element of anу IoT solution is to pick an appropriate programming language that ensures the interaction between IoT devices and apps, processing, data storage, task execution, and user interaction.

4 Key Types of Event-Driven Architecture

Adam Bellemare compares four main types of Event-Driven Architecture (EDA): Application Internal, Ephemeral Messaging, Queues, and Publish/Subscribe. Event-Driven Architectures have a long and storied history, and for good reason. They offer a powerful way to build scalable and decoupled architectures. But thanks to its long history, people often have different ideas of what EDA means depending on when they first encountered this architecture.