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Problem-Solving Strategies for Data Engineers

via LinkedIn Learning

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Data engineers are facing a wide variety of problems every day. Learn best practices on how to approach the typical challenges.

Syllabus

Introduction

Introduction
What you should know

1. Roles and Phases

The data engineer
All important data engineering project phases
General challenges faced

2. Planning

Understanding the status quo
Collecting the right requirements
Defining good KPIs

3. Design

Keeping implementation efforts in mind
Choosing the right architecture and framework
Predicting costs and scaling better
The right benchmarking of existing tools

4. Implementation

Definition of work packages and responsibilities
Risk assessment
Testing the right parts
Having a good documentation

5. Operations

Approaches to monitoring
Approaches to bug fixing
Awesome training of staff, current and new
How to improve processes

Conclusion

Conclusion and outlook

Taught by

Andreas Kretz

Reviews

4.6 rating at LinkedIn Learning based on 82 ratings

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