Coursera Plus Annual is 40% Off — Ends July 13.

Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

LinkedIn Learning

Problem-Solving Strategies for Data Engineers

via LinkedIn Learning

Write review
Simplilearn Ad

Earn a Michigan Engineering AI Certificate — Stay Ahead of the AI Revolution

Learn More → Coursera Ad

AI, Data Science & Cloud Certificates from Google, IBM & Meta

Learn More →

Overview

Google, IBM & Meta Certificates – 40% Off
One plan covers every Professional Certificate on Coursera.
Unlock All Certificates
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

Start your review of Problem-Solving Strategies for Data Engineers

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free
Someone learning on their laptop while sitting on the floor.