Session Outline
Many companies have challenged themselves to succeed with digital transformation, which is a new area without best practices, common language and clear measures of success. I will address how we at Grundfos have tried to mature and improve our data projects by writing a Data Pipeline Playbook and organizing Data Engineers in a Data Pipeline Community. I want to describe the reasoning behind these approaches and the technical goals.
Key Takeaways
- Maturity of a Digital Transformation
- Creation of a common language
- Data foundation for AI projects
- Technical goals of a Data Pipeline
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Bio
Lotte Ansgaard Thomsen – Lead Big Data Engineer | Grundfos
Lotte has previously worked as a researcher at Yale University investigating and analyzing data from CERN. More than 10 years of experience of working with one of the world largest dataset has given her a deep knowledge of what is important to get a solid data foundation for successful IOT/AI projects . The last two years she has been working at Grundfos: using the obtained knowledge to create guidelines for data pipelines, data quality and data architecture. She believes that with collaboration and proper data handling the world can be improved with the new capabilities
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