Data Platform

Your machine data,
in the right environment.

After integration, the next question is where the data should live. StriData can host the platform for you, or deploy it in your own cloud or self-hosted environment on Azure, AWS, Google Cloud, on-premises, or equivalent, with data ownership aligned to your IT landscape.

Request Quick Scan Talk to us
1500+ machines structured across deployments
Used across 40 countries
Azure, AWS, GCP, self-hosted supported
Why it matters

Where your data lives shapes what you can do with it.

The integration itself is only part of the design. Where the data platform runs, and how it is managed, affects ownership, integration options, operating cost, and how easily it fits into the rest of your reporting and analytics landscape.

Ownership and control

Some OEMs want a managed setup with minimal overhead. Others need the data platform to run fully inside their own cloud or self-hosted environment, with their own policies for access, security, and retention.

Integration with business systems

Machine data becomes more useful when combined with ERP, CRM, service, or MES data. That is easier when the platform runs inside, or close to, the systems your IT and data teams already use.

Cost at scale

A setup that works for a pilot does not always work for 50 customers or 1500 machines. Infrastructure, processing, and support behave differently once the rollout grows across environments and customers.

Two deployment models

Hosted by StriData, or inside your environment.

The architecture and data model stay the same. The difference is where the platform runs, who manages it, and how closely it connects to your internal systems.

Managed

Hosted by StriData

StriData runs and maintains the data platform for you, so your team can focus on using the output instead of managing infrastructure.

  • Fastest route to a working reporting and analytics layer
  • Minimal involvement required from your IT team
  • Good fit for pilots, first rollouts, or lean teams
  • Centralized management of storage, transformation, and model updates
  • Consistent output ready for reporting and further analysis
Best fit when

you want to move quickly, keep infrastructure overhead low, and avoid setting up your own hosting environment upfront.

Customer-hosted

Deployed in your environment

StriData deploys the platform inside your own cloud or self-hosted environment, aligned with your IT standards and data governance.

  • Deploy in Azure, AWS, Google Cloud, on-premises, or other self-hosted environments
  • Data stays fully within your own infrastructure and access model
  • Easier integration with ERP, CRM, MES, and internal data platforms
  • Fits existing security, compliance, and governance requirements
  • Strong foundation for broader data and AI initiatives
Best fit when

your IT team wants control, integrations with internal systems matter early, or machine data needs to become part of your wider data landscape.

How it works

The same architecture, wherever it lives.

The deployment choice changes the environment, not the logic. The machine data still moves through the same core steps before it becomes usable for reporting, service, and analytics.

1

Machines and gateways

Data originates from PLCs, machine controllers, sensors, and connected gateways already present in the field.

2

Ingestion

Data is extracted and structured into a consistent pipeline, ready for storage and further processing.

3

Storage

Data lands in the selected environment, such as Azure, AWS, Google Cloud, on-premises infrastructure, or a managed StriData setup.

4

Modeling

Raw machine signals are transformed into a structured model with clear KPI definitions, states, alarms, and context.

5

Reporting

The output feeds dashboards, customer-facing reporting, service views, and future analytics or AI use cases.

Hosted by StriData means StriData manages the storage and processing environment for you. Deployed in your environment means the same architecture runs inside your own cloud or self-hosted setup, aligned with your internal IT standards and integrations.

Comparison

Which model fits your situation?

Consideration Hosted by StriData Your environment
Time to first dashboard Usually the fastest route, with less internal setup required. Often slightly longer, due to tenant setup, access, and internal alignment.
Data ownership Operationally managed by StriData, with agreed ownership and access boundaries. Stored and governed directly inside your own environment.
Integration with ERP, CRM, MES Possible, but depends on external connectivity and project scope. Usually more natural, especially when those systems already live in your cloud, on-premises, or self-hosted environment.
Cost model More managed-service oriented, with less internal infrastructure overhead. More infrastructure responsibility on your side, but often stronger alignment with existing IT investments.
Required IT capacity Low to moderate. Internal IT involvement can stay limited. Moderate to high. Your team typically supports access, hosting, and governance decisions.
Suitable for AI Yes, when the use case is scoped and the data model is in place. Yes, especially when machine data needs to feed a wider company data and AI stack.
Switching later Possible. A managed start can be migrated later into your own environment. Possible. Starting internally gives maximum control from day one.
Questions

About deploying in your environment

Most technical questions here are about ownership, hosting choices, and how the platform fits into existing IT standards. These are usually the first points teams want to validate before deciding how the environment should be set up.

Yes. If you choose customer-hosted deployment, the platform runs in infrastructure that belongs to you or is managed on your behalf inside your own setup. That can be an Azure subscription, AWS account, Google Cloud project, an on-premises environment, or a self-hosted setup.
StriData is not tied to one cloud vendor. Typical deployments use Azure, AWS, Google Cloud, self-hosted, or on-premises environments, depending on what best fits the customer landscape and integration requirements.
Data ownership is defined clearly in the project setup. In a customer-hosted model, the platform sits directly under your control. In a managed model, StriData operates the platform while ownership, access, and usage boundaries are agreed upfront.
Yes. That is a common route when speed matters first and internal platform decisions come later. The model, pipeline logic, and reporting structure can be designed so migration remains practical once the use case is established.
No, not in principle. The deployment decision is about where the data platform lives after integration. It does not mean StriData takes over router setup or device template configuration. Existing machine connectivity remains the starting point.
Security is handled according to the selected model. In customer-hosted deployments, the platform follows your own policies for identity, access, networking, logging, and retention. In managed deployments, the setup and responsibilities are defined explicitly as part of the project scope.
Typically through a focused technical alignment process. StriData scopes the required components, access, and interfaces, then works within the standards your IT team already uses. The goal is not to introduce a separate platform choice, but to fit the machine data layer into the environment that already makes sense.

Want to discuss your setup?

Every machine environment is different. We can walk through your current architecture, data sources, and constraints — and show how your data can be structured into a reusable layer.

StriData has structured analytics for 1500+ machines across 40 countries, all built on existing connectivity, without replacing infrastructure.

Martijn van Dijk

Founder & Data Engineer