Breaking down data silos with data-driven process engineering
In an era dominated by cross-organizational software systems and platform-based information architectures, it is crucial to refocus on business processes and the value creation model. However, so-called data silos—which refer to isolated collections of data that are not shared with other data systems or departments—often stand in the way.
In this training, we’ll introduce you to a specific method of data-driven process engineering. Through hands-on exercises, you’ll learn how to break down data silos and ensure a structured flow of information. Participants will be actively involved in applying the method and will gain valuable insights into its practical implementation.
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- You will gain methodological knowledge on problem analysis, solution structuring, and planning your approach to digital transformation, specifically in the context of breaking down data silos
- You will learn about practical examples of digitalization projects that effectively break down data silos and optimize operational processes and information systems
- By applying a process analysis method as an example, you will gain the necessary skills and gain insight into the toolkit of data-driven process engineering
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This training is designed for specialists and managers involved in the analysis, design, or optimization of business processes and data flows, in particular:
- Business analysts and process managers
- IT and data managers
- Project managers and digital transformation leads
- Department representatives from manufacturing, energy, automotive, and other sectors
- Decision-makers in transformation and digitalization initiatives
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- Format: webinar / lecture / training / workshop
- Duration: flexible
- Delivery: online or in-person
- Practical component: high, with examples and concrete application scenarios
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The format can be customized to suit your organization’s specific needs—for example, by:
- Incorporating your specific use cases
- Adapting to your industry or project type
- Delving deeper into specific methods or tools
