Learn the differences between batch and real-time data processing, and explore the decision-making factors for choosing the right approach to optimize data pipelines.
Learn more about Apache Flink, a powerful stream processing tool, for building streaming data pipelines, real-time analytics, and event-driven applications.
Retrieval augmented generation (RAG) needs the right data architecture to scale efficiently. Learn how data streaming helps data and application teams innovate.
AI and LLMs streamline user story creation, optimize backlog, and predict trends, improving agile product development speed, relevance, and user engagement.
Learn how to handle schema versioning and updates in Kafka and other event streaming platforms without using schema registries through custom deserializers.
Unravel the complexities of streaming data joins in this guide covering key concepts, design, and best practices for optimal real-time data enrichment.
Discuss the strategic importance of Spark code upgrades and explore an introduction to a powerful toolkit designed to streamline this process: Scalafix.
Let's explore the features, applications, and top choices for microcontrollers in industrial IoT, achieving reliability, efficiency, and security in harsh environments.
Real-time anomaly detection using LLMs enhances accuracy for finance, healthcare, and cybersecurity through contextual analysis and pattern recognition.
While individual components like Kafka, Flink, and Pinot are very powerful, managing them at scale across cloud and on-premises deployments can be operationally complex.
Explore the latest advances and future trends in data warehousing technologies, highlighting the innovations that are shaping the next generation of data warehouses.
This guide will walk you through the essential steps to build your first IoT project, ensuring you have a solid foundation to explore this fascinating field.