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
Overview
Syllabus
Introduction
Presentation Overview
Locations
The BMW Group
BMWs Big Data Journey
BMWs Big Data Mission
Projects
Platform
Platform Architecture
Business Model Problems
HighLevel Architecture
Backend Shadow
Type Ontology
Query
Model interoperability
Hybrid environments
Data creation
Data privacy
Data security
Who owns the data
Data collection
Why Tesla
Audience Question
Advice for Data Scientists
Taught by
WeAreDevelopers
