Digital Data

Sources, Formats and Considerations for Use in Data-Driven Modelling

Sources, Formats and Considerations for Use in Data-Driven Modelling

Data-driven modelling is a key component of what is commonly referred to in industry as ‘Digitalisation’, ‘Condition-based monitoring (CBM)’ and ‘Industry 4.0’. However, each end-user who wishes to embrace such concepts will have their own bespoke data sources. Whether it’s a newly commissioned facility or an older one, the types of sensors and their associated data networks will differ from one site to the next. The storage of this data will also vary- for example, it is still common for many sites to store their data in excel spreadsheets, whereas more modern applications will likely use well-structured databases. The data can be labelled or unlabelled, which in turn informs the type of modelling to be performed (supervised or unsupervised). Data driven modelling can be applied to all these variations and more. Whether it’s aimed at analysing historical data or live streamed data, end-users can improve their own understanding of their facility processes and ultimately implement more efficient work patterns.

This webinar, presented by Head of Digital Services, Dr Gordon Lindsay, will examine crucial data considerations which should be addressed when implementing a digitalisation strategy.

The webinar will be of interest to facility owners, control and instrumentation engineers, small start-up companies who require assistance in interpreting large data sets, and anyone who is implementing a digitalisation strategy.

This Webinar Will Focus on These Points

  • How data driven models can be tailored to a client’s specific data set
  • How to support a client’s needs in both historical and live data analysis/modelling
  • The difference between modelling with labelled and unlabelled data

About the Speaker

Dr Gordon Lindsay
Head of Digital Services

Over the last 10 years, Dr Gordon Lindsay has been one of the lead design engineers of TÜV SÜD National Engineering Laboratory’s Control and Instrumentation Systems within their fluid flow research laboratories.

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