We talked about:

• Andreas’s background
• Why data engineering is becoming more popular
• Who to hire first – a data engineer or a data scientist?
• How can I, as a data scientist, learn to build pipelines?
• Don’t use too many tools
• What is a data pipeline and why do we need it?
• What is ingestion?
• Can just one person build a data pipeline?
• Approaches to building data pipelines for data scientists
• Processing frameworks
• Common setup for data pipelines — car price prediction
• Productionizing the model with the help of a data pipeline
• Scheduling
• Orchestration
• Start simple
• Learning DevOps to implement data pipelines
• How to choose the right tool
• Are Hadoop, Docker, Cloud necessary for a first job/internship?
• Is Hadoop still relevant or necessary?
• Data engineering academy
• How to pick up Cloud skills
• Avoid huge datasets when learning
• Convincing your employer to do data science
• How to find Andreas

Links:

• LinkedIn: https://www.linkedin.com/in/andreas-kretz
• Data engieering cookbook: https://cookbook.learndataengineering.com/
• Course: https://learndataengineering.com/

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