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1
Introduction
2
Presentation Overview
3
Locations
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The BMW Group
5
BMWs Big Data Journey
6
BMWs Big Data Mission
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Projects
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Platform
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Platform Architecture
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Business Model Problems
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HighLevel Architecture
12
Backend Shadow
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Type Ontology
14
Query
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Model interoperability
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Hybrid environments
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Data creation
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Data privacy
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Data security
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Who owns the data
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Data collection
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Why Tesla
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Audience Question
24
Advice for Data Scientists
Description:
Explore the journey of the BMW Group in developing data-driven ecosystems for the automotive industry in this 43-minute conference talk from WeAreDevelopers. Delve into the established technology stack, challenges encountered, and novel machine learning applications deployed in real-world environments. Gain insights into gradient boosting and convolutional neural nets use cases. Discover BMW's Big Data mission, platform architecture, and solutions to business model problems. Learn about data creation, privacy, security, and ownership in the automotive context. Understand the importance of query model interoperability and hybrid environments in BMW's data ecosystem. Conclude with valuable advice for aspiring data scientists in the automotive field.

Data-Driven Ecosystems in the Automotive Industry

WeAreDevelopers
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