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Incomplete data is as worthless
as no data

Most data historian software doesn’t capture sufficient data for advanced analytics.

A new approach to data historian software

Data acquisition and storage that’s built for analytics

The vast amount of time-series data being produced by industrial processes has surpassed the capability of traditional data historian software. Scalability, reliability, and integrity constraints leave many businesses without a reliable source of data, limiting the ability to apply analytics and gain critical insights.

At VROC the most common issue among our clients is their data quality. Many unfortunately find it extremely difficult to extract the data to begin with, and once extracted they discover it is incomplete and unreliable.

VROC has heard the cries of our data engineers and IT managers and designed a distributed micro-services data historian for industrial big data, DataHUB4.0, so our clients can start collecting, storing and securing all their historical and live data one location where their team can readily apply advanced analytics.

Discover DataHUB4.0
Product Features

Why our customers choose VROC

Scalable Storage

Modern microservices data storage for enterprise scalability and real-time data reliability.

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Interoperability icon

Interoperability

VROC has no set alliance with any equipment or sensor provider and is focused on interoperability, even with legacy systems, to help you achieve your business objectives.

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Data Ownership

Retain complete ownership and control of your data with flexible hosting solutions available.

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Data Integrity

VROC automatically verifies your data quality, alerting you if there is a problem.

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Data Storage Cost Minimisation

No excuse for incomplete data

Data storage costs have reduced significantly over the last few years; however many data historians software companies rely on complex infrastructures, charge individual user license fees and charge for the volume of data being collected and stored. This structure increases the overall cost and forces some businesses to reduce the volume of data that they collect and store, for example some companies only collect data from a failure, rather than their steady state data.

For artificial intelligence to produce continuous valuable insights for any organisation, that organisation needs to collect and store all operational data. The AI continuously learns from all the available data, detecting minute changes in conditions and correlations between seemingly unconnected processes, providing critical insights and alerts in advance. Without quality data AI cannot provide accurate insights.

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Get started with VROC today

Ready to embark on a pilot project or roll-out the innovation enterprise wide? Perhaps you need assistance integrating your systems or accessing your data? We have a solution to help you as you progress through your digital transformation.