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DIGITAL TRANSFORMATION

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The road to Industry 4.0: Digitalisation of industrial companies step by step – Interview with Sándor Gáspár

Industry 4.0 has become an inescapable concept in recent years. It is an objective for companies to integrate modern business intelligence systems into their operations as much as possible and join the smart factory revolution. Of course, the digitalisation of an industrial company cannot be done in all areas at the same time. Indeed, there is a classic three-level approach to the digital transformation of manufacturing companies, which should be kept in mind for success. The so-called entry level is ERP, followed by MES and then SCADA.

Út az Ipar 4.0 felé: iparvállalatok digitalizációja lépésről lépésre – Interjú Gáspár Sándorral

Industry 4.0 has become an inescapable concept in recent years. It is an objective for companies to integrate modern business intelligence systems into their operations as much as possible and join the smart factory revolution. Of course, the digitalisation of an industrial company cannot be done in all areas at the same time. Indeed, there is a classic three-level approach to the digital transformation of manufacturing companies, which should be kept in mind for success. The so-called entry level is ERP, followed by MES and then SCADA.

But what exactly do you need to know about these levels and how can you minimise failure during the project? In Trend FM’s Afternoon Monitor programme, András Érczfalvi hosted Sándor Gáspár, Head of Data Solutions Competence Center at Stratis, for an exciting discussion.

Listen to our latest audio recording and explore with an expert the steps of digitalisation of industrial companies and the importance of the role of data!

Click on Play and plan ahead with Stratis!

About author

Gaspar Sandor Szerzo
Sándor Gáspár

Head of the Artificial Intelligence Competence Centre

Analytics - Data Solutions

Gáspár Sándor has been leading Stratis' artificial intelligence division since 2020, bringing over 20 years of experience in data science. Together with his team, he develops machine learning-powered decision support solutions for large enterprises, leveraging our clients' existing data assets. Additionally, he assists in automating our clients' existing processes using deep neural networks-based NLP and machine vision solutions.

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