Enhancing Data Quality in MQTT-Based IoT Data Pipelines
In IoT and IIoT environments using MQTT brokers for data transmission, data producers continuously dispatch MQTT messages across diverse topics. At the same time, a variety of services harness this data to construct the essential application logic, commonly known as a data pipeline.
In an enterprise set-up, the sheer number of data producers and consumers can be staggering, reaching millions in some instances. Managing this vast ecosystem presents significant challenges, and enforcing certain behaviors is necessary to keep producers and consumers decoupled and to enhance the resilience of data pipelines. We have you covered to address this challenge.
Watch Stefan Frehse, Engineering Manager at HiveMQ, Michal Piasecki, Product Manager at HiveMQ, and Michael Parisi, Product Marketing Manager at HiveMQ, delve into the world of MQTT data management with a focus on maximizing data quality and integrity. In this session, we will explore how schema validation and policy enforcement capabilities within an MQTT broker ensure data quality and integrity, ultimately maximizing the business value of the data.
**** Contents of the Webinar ****
00:00 – Introduction
02:06 – Importance of Data Quality
03:39 – MQTT and Data Quality
05:04 – MQTT Data Validation Using Schemas and Policies
09:34 – How to Maximize the Business Value of Your Data using HiveMQ Data Hub
12:40 – Use Cases Discussing Why You Need Clean Data
19:34 – Demo
38:59 – Q&A
**** Resources***
HiveMQ Data Hub: https://bit.ly/45cr03O
Get HiveMQ Broker: https://bit.ly/3F1RudC
HiveMQ Control Center: https://bit.ly/48xXmcg
White Paper | Measuring the Quality of Your Data Pipeline: https://bit.ly/3PEFGmR
#datapipeline #mqtt #iot