Breakout Session: DataOps for digital twins

First mentioned in early 2000, in the context of the manufacturing domain, the Digital Twins (DT) concept is gaining wider acceptance today as the definite next step in leveraging data as both a strategic and tactical asset. Real-time data is the key requirement for continuously improving and highly sustainable DT applications. This has been made possible largely by the recent advances in data and computing – including but not limited to, performant data pipelines, big data architectures, data management, cloud-based as-a-service models, artificial intelligence, and advanced analytics (predictive and prescriptive). This advent of analytics and numerical simulations in the operational and monitoring phase of a product lifecycle reinforces the need for trusted real-time data. 

This talk will focus on how data management plays a critical role in the core functions of DTs and helps refine the quality of the data assets. The trust and quality of the data need to be maintained and tracked over time by establishing data governance policies and processes. The need for scalable solutions will be stressed – to be specific, the accelerating need for any organization to include a data catalog with automated metadata management as well as lineage for dependency analysis as part of its data strategy.