Poor data quality costs organizations millions each year, increasing complexity and hindering decisions (Gartner)
62% Higher Revenue
Companies successfully operating in real-time environments outperform competitors (MIT)
30% Faster Decisions
Organizations utilizing live data insights improve their decision-making speed (Deloitte)
Why Real-time Distributed Data Intelligence?
Organizations are generating more operational data than ever, but to drive real business impact, they need to extract value quickly and make that data AI-ready.
Why Real-time: Decisions need to happen the moment events occur, not hours or days later. Delayed insights are missed opportunities.
Why Distributed: We live in a distributed world, data is created everywhere, from edge devices to factories to cloud systems. Instead of moving everything to a centralized cloud, extract insights where the data lives.
Why Intelligence: Raw data isn’t enough. You need intelligence layered on top to deliver operational insights that inform action, unlock efficiency, and enable better business outcomes.
HiveMQ Pulse Key Benefits
HiveMQ Pulse is a real-time distributed data intelligence platform that provides insights at the source, precisely where they have the most impact.
Ensure data consistency by cataloging, transforming, and governing information in a unified namespace, enabling interoperability, standardization, and OT-IT integration.
Real-time Actionable Insights
Process and contextualize data in motion to reduce delays, improve efficiency, minimize downtime, and drive faster, data-driven decisions.
Distributed Intelligence
Reduce latency and enable real-time automation by integrating a calculation engine and AI/ML models at the edge for enhanced predictions and optimized workflows.
AI-Ready
Deliver complete, reliable data from edge to cloud for seamless AI integration. Govern and contextualize data at the source to improve model accuracy and accelerate insights.
As UNS evolves it will drive deeper integration, smarter operations,and significant innovation across industrial ecosystems.
Anand Taparia
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Principal Analyst, IoT Analytics
HiveMQ Pulse Technical Architecture
With a flexible architecture uniquely suited to support a Unified Namespace (UNS) approach, HiveMQ Pulse allows you to manage, transform, govern, and derive insights from distributed devices and systems, providing a single, structured view of operational data across the enterprise.
Pulse Client
Secure graphical web app that interfaces with the Server to visualize, query, and manipulate the data models, provide dashboards, and facilitate interaction.
Pulse Server
Acts as an orchestrator, responsible for knowing where the data is, managing information models, authorizing agents, and orchestrating queries.
Pulse Agent
Indexes and processes edge data with a distributed calculation engine. Filters, historicizes, and governs in-flight messages while enabling real-time queries and compute tasks.
HiveMQ Pulse Key Technical Capabilities
Manage, transform, govern, and derive insights from distributed devices and systems with a single view of operational data across the enterprise.
Historical Analysis: Make decisions rapidly with the ability to store and analyze specific data sets where they are generated.
UNS Data Catalog: Organize and standardize data into a consistent, queryable structure accessible across the enterprise.
Real-time Events: Leverage an enterprise-grade MQTT backbone for scalable, event-driven data streaming from edge to cloud.
IoT Streaming Governance: Transform data in flight, passing only the most relevant, contextualized data to cloud and enterprise systems.
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