Practical DevOps for Big Data Course

Welcome to Practical DevOps for Big Data's Online training with live Instructor using an interactive cloud desktop environment DaDesktop.

Experience remote live training using an interactive, remote desktop led by a human being!

7 hours
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Course Overview

This instructor-led live training is designed to provide participants to gain mastery on practical devops for big data. You will learn the fundamentals of practical devops for big data and with greater emphasis on the functionality and application to your work or study.


This course is about a methodology for constructing big data applications. A methodology exists for the purpose of solving software development problems. It is made of development processes—workflows, ways of doing things—and tools to help concretise them. The ideal and guiding principle of a methodology is to facilitate the job and guarantee the satisfaction of stakeholders involved in a software project—end-users and maintainers included. 


  • Introduction
  • DevOps and Big Data Modelling
  • Modelling Abstractions
    • Introduction to Modelling
    • Platform-Independent Modelling
    • Technology-Specific Modelling
    • Deployment-Specific Modelling
  • Formal Quality Analysis
  • From Models to Production
  • From Production Back to Models
    • Monitoring
    • Anomaly Detection
    • Trace Checking
    • Iterative Enhancement

Course Category: DevOps

What you get

Money back guarantee

If the course you selected doesn't have a trainer available on your preferred schedule, you may withdraw your payment.

Remote session with live human

Trainings are not pre-recorded video. You may interact with your instructor in real-time.

Instructor access to revolutionary training environment DaDesktop

DaDesktop is an interactive cloud desktop environment solution for trainers and participants.

Training materials

Certificate of course completion

Entry in certified person catalog

Course Schedule

09:30 - 16:30 EST
09:30 - 16:30 EST
09:30 - 16:30 EST
09:30 - 16:30 EST
09:30 - 16:30 EST
09:30 - 16:30 EST