Learn how to build fault-tolerant, reactive event-driven applications using Spring WebFlux, Apache Kafka, and Dead Letter Queue to handle data loss efficiently.
Dark data is the vast amounts of unstructured information collected by organizations that often go unused. It includes emails, customer interactions, sensor data, etc.
To make long-term trend analysis easier, we can leverage datelists, where we store each metric value corresponding to a date in an array in a sequential manner.
A Data-First IDP integrates governance, traceability, and quality into workflows, transforming how data is managed, enabling scalable, AI-ready ecosystems.
Learn to implement Slowly Changing Dimension Type 2 (SCD2) in a data warehouse for tracking historical data, ensuring data integrity, and enabling scalability.
This article introduces process mining, explaining its key elements and practical applications for discovering and analyzing workflows using event data.
This article examines how QML can harness the principles of quantum mechanics to achieve significant computational advantages over classical approaches.
Gain insight into key Iceberg features such as time travel, schema evolution, partition evolution, and ACID transactions with clear SQL examples and diagrams.
Learn more about how WebRTC's triple-layer security architecture protects IoT communications and creates the building blocks of secure device interactions.
Navigate privacy, security, and compliance challenges for innovation. Effective data governance is now more critical due to recent generative AI developments.
Big data isn’t dead; it’s just going incremental. But bad things happen when uncontrolled changes collide with incremental jobs. Reacting to changes is a losing strategy.
The three data storage options and their pros and cons: the legacy data warehouse, the more recent data lake, and contemporary data lakehouse architectures.
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