Optimizing Sparkplug with HiveMQs Data Hub Module

In complex industrial environments, such as smart manufacturing, or energy production and distribution, managing data presents significant challenges. Data is spread across different platforms, devices, and applications, and often involves compatibility issues, rigid protocols, and excess data that’s tough to manage. See how Shashank Sharma introduces the HiveMQ Sparkplug Module for Data Hub, and explains how it overcomes these challenges by - Migrating Protobuf into human-readable JSON data - Metrics fan-out enables more fine-grained topic structures - Ensuring data quality through schema validation *** RESOURCES *** – Read Shashank Sharma´s blog post "Overcoming MQTT Sparkplug Challenges for Smarter Manufacturing": https://bit.ly/3YxctiU – Learn about HiveMQ MQTT Broker: https://bit.ly/3QbPaq3 – Read more about MQTT Sparkplug in this blog series: https://bit.ly/3jg2Lgx Timestamps: 00:11 Introduction 00:39 Today´s Challenges in Smart Manufacturing 01:06 MQTT and the Publish/Subscribe Communication Model 01:27 The Unified Namespace 01:46 Key Enhancements in Sparkplug 02:12 Extending the Adoption of Sparkplug in Industrial Environments with Sparkplug Module for Data Hub 03:57 Demo: Sparkplug Module in Action #sparkplug #iot #datahub #mqtt