Skip to main content
+49 721 9654-724

IoT Data Hub · Data Foundation

Connect machine data once. Reuse it in a controlled manner.

A robust data foundation is essential for dashboards, analytics, AI notebooks, and AI pipelines. Bytefabrik integrates machine data from various protocols, standardizes it, and makes it available in a controlled manner for further applications.

Request a 30-minute demo

Part of the IoT Data Hub

Diese Fähigkeit arbeitet auf derselben Konnektivität, Semantik, Historie und Governance wie alle Data-Hub-Werkzeuge.

Product Overview →

When Every New Machine Becomes Yet Another Integration Project

Connectivity can only serve as a solid foundation when technical connectivity, business context, and rollout are addressed together.

Industrial Control and Network Infrastructure in a Manufacturing Facility
Heterogeneous OT. A controlled database.
  1. 01

    Protocols and generations of machines differ

    Control systems, sensors, and existing systems provide data via different interfaces, structures, and update rates.

  2. 02

    Raw signals lack technical context

    A value becomes usable only when it has been reliably assigned to a unit, facility, station, process step, and meaning.

  3. 03

    A successful pilot program can't simply be copied

    Manual configurations and custom mappings prevent additional machines or lines from being connected in a controlled manner.

  4. 04

    OT networks require flexible operating models

    Segmentation, limited connectivity, and data sovereignty require edge, on-premises, and distributed deployment options.

End-to-End Data Path

From Data Source to Reusable Data Product

The IoT Data Hub does more than just connect machines. It brings together connectivity, harmonization, context, and future use within a single, integrated model.

  1. 01

    Data Source

    Connect controllers, sensors, gateways, and existing systems.

    S7 · OPC UA · MQTT · IO-Link · REST

  2. 02

    Connection

    Capture signals, verify them, and transmit them securely to the platform.

    Edge · On-Premise · Centrally Managed

  3. 03

    Harmonization and Context

    Transform data and map assets, units, and semantics.

    Mappings · Assets · Metadata · History

  4. 04

    Data product

    Reuse the same data source for dashboards, analytics, APIs, and AI.

    Charts · AI Notebooks · AI Pipelines · Insights

Data Onboarding as a Controlled Product Workflow​

The product views show how an industrial source is built, from the initial connection to the reusable rollout model.

How does a machine connection become a scalable data product?

Connect to a source

Configure an Industrial Connection (Guided)

Adapters guide users through connection parameters, security, and the selection of relevant signals. Existing industrial protocols can be configured without the need for a custom integration interface.

OPC UA · MQTT · S7 · Modbus · IO-Link · REST

Understanding Platform Architecture
Selecting and Configuring an Industrial Data Source
Product View
Platform Capabilities

What turns a connection into a robust data foundation.

  1. Industrial Connectivity

    Open protocols and adapters for controllers, sensors, and existing systems.

  2. Semantic Context

    Assets, units, and metadata give each signal a reusable meaning.

  3. Controlled Operation

    Roles, versioning, and traceable changes for production environments.

  4. Repeatable Rollout

    Templates and remote deployment for machines, production lines, and multiple locations.

  5. Open to Applications

    Provide the same data source for dashboards, analytics, APIs, and AI.

From the first adapter to full rollout

The expansion relies on reusable structures rather than constantly creating new, standalone integrations.

  1. 01Pilot

    Connect a relevant data source

    Connections, signals, and the technical target context are validated on a specific machine.

  2. 02Template

    Making the Configuration and Model Reusable

    Proven parameters, mappings, and asset structures are saved as controlled templates.

  3. 03Line

    Roll out the same machine types consistently

    Templates speed up additional connections and reduce discrepancies between installations.

  4. 04Multi-Site

    Manage locations centrally, operate them locally

    Distributed instances, roles, and deployments create a common framework for the full rollout.

Frequently Asked Questions About Architecture

Does the connectivity fit into our OT and IT environments?

Does production data have to leave the factory?

No. Connections and data processing can be handled close to the edge or entirely on-premises. Centralized or cloud-based components are only used where architecture and governance permit.

Do existing systems need to be replaced?

No. The IoT Data Hub connects control systems, gateways, historian systems, and line-of-business applications and presents their data in a unified context.

How are proprietary data sources integrated?

In addition to existing adapters, proprietary sources can be integrated via open APIs and the Developer SDK. The new connection then uses the same models and operating mechanisms.

How does a pilot program become a resilient rollout?

Configurations, mappings, and asset models are reused as versioned templates. Remote deployment and centralized governance reduce the manual effort required for additional machines and locations.

30-minute product demo

Which machine would you like to connect first?

We'll demonstrate live how a specific data source is connected, harmonized, and made available for dashboards, analytics, and AI. A concise session that requires no preparation.

Product demo with a specific data source
Request a 30-minute demo
Networked Production Line with Industrial Data Infrastructure