Problem-Solving Strategies for Data Engineers
1h 56mBeginner2023-06-30
Authors

Andreas Kretz
Founder of Learn Data Engineering
Course details
Data engineers face a wide variety of problems every day—and often variations of the same problems. In this course, data engineer Andreas Kretz takes you through a variety of common problems you may face and shares her problem-solving strategies for typical problems within all phases of engineering projects. Andreas teaches you how to recognize which phase of a data project you’re in—planning, design, implementation, and operations—and shares solutions targeted to problems you may encounter in each phase. Andreas teaches you how to identify key knowledge performance indicators (KPIs) in planning, how to predict costs and scale better in the design phase, explains why and how to do a risk assessment, and shares some tips on bug fixing and ways you can improve your process. If you’re looking for better ways to deal with data engineering issues, join Andreas in this course to take your problem-solving skills to the next level.
Skills covered
Decision-MakingData EngineeringData ScienceProfessional DevelopmentLeadership and ManagementOne-Off
Concepts
Introduction
- Introduction
- What you should know
Roles and Phases
- The data engineer
- All important data engineering project phases
- General challenges faced
Planning
- Understanding the status quo
- Collecting the right requirements
- Defining good KPIs
Design
- Keeping implementation efforts in mind
- Choosing the right architecture and framework
- Predicting costs and scaling better
- The right benchmarking of existing tools
Implementation
- Definition of work packages and responsibilities
- Risk assessment
- Testing the right parts
- Having a good documentation
Operations
- Approaches to monitoring
- Approaches to bug fixing
- Awesome training of staff, current and new
- How to improve processes
Conclusion
- Conclusion and outlook