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ThingWorx Analytics TTPSC

What is ThingWorx Analytics?

Analytics

ThingWorx Analytics is an integrated module of ThingWorx Platform that allows you to quickly and easily detect issues and anomalies in real time.
It offers predictive anaytics and the possibility to create simulations for future and planned solutions. It’s a product designed for an easy and quick to use interface. Native integration with the IoT Platform – ThingWorx allows you to take advantage of the possibilities of data analysis and machine learning in any IoT system and with any set of data.

Why us?

Transition Technologies PSC belongs to the Transition Technologies Capital Group which was established in 1991 and has been continuously expanding since then. Today we employ almost 2 000 experts who develop and create state-of-the-art solutions for businesses. We operate on three continents: Europe (Poland, Scandinavian countries, France, Germany and Ukraine), the USA and Asia (Taiwan, Japan). We are partnered with the largest suppliers in the IT industry, including Microsoft, Google, PTC, Atlassian, AWS Azure and Oracle.

TTPSC team

We have

KNOWLEDGE

Our realizations:

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Do you need a free consultation? Contact one of our global representatives

North America

Nate Taylor TT PSC

Nate Taylor

Director of Sales

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Germany

Andreas Kratz TT PSC

Andreas Kratz

Business Development Manager

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Taiwan

Candy Chao TT PSC

Candy Chao

Head of TTPSC Asia

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France

Mohamed Ennassiri TT PSC

Mohamed Ennassiri

Business Development Manager

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Poland

Radosław Kowalczyk TT PSC

Radosław Kowalczyk

Strategic Customers Manager

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Why ThingWorx Analytics?

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Predictive modelling

Enables supervised machine learning for industrial IoT solutions and expands data analytics capabilities with automatic predictive modelling – without the need to use expertise in machine learning algorithms.

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Descriptive analytics

Enables a better understanding of industrial data, providing a range of advanced algorithms that allow users to discover useful patterns and correlations in data.

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Real-time monitoring

Monitors data streams using various statistical techniques and machine learning to teach the predictive data assessment model. It anticipates future results and offers the possibility to make appropriate forecasts based on these results.

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Prescriptive scoring

Improves future performance and results by automatically running simulations to generate recommendations that optimise product and process performance.

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Digital simulation

Uses integrated models and other computing providers in the application to simulate the behaviour of physical products in the digital world.

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