Serverless Data Processing with Dataflow: Operations

In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance.

Pluralsight Teams₹4,166.75 per user/month, billed annually
₹50,004
CompleteBilled Monthly
₹2,370/mo

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Course Insight

Designed for advanced/expert practitioners. Designed for experienced practitioners. We recommend having a solid grasp of Data Science fundamentals before starting this specialization.

Advanced LevelSelf-Paced Learning

SKILLS TO
MASTER

Analytics
Exploratory Data Analysis
ModelingTrending
Predictive Machine Learning
SQL Querying
Relational Data Management
Pandas
Matplotlib
Statistics
Tableau
ETL
Careers:Relevant for professionals pursuing roles within Data Science.

Quick Facts

Below sections are verified from last major sync. For real-time updates and today's latest lectures, Check official page here.

What You’ll Learn

  • Introduction : 2mins.
  • Monitoring : 17mins.
  • Introduction : 2mins.
  • Logging and Error Reporting : 7mins.
  • Monitoring : 17mins.
  • Troubleshooting and Debug : 12mins.
  • Logging and Error Reporting : 7mins.
  • Performance : 13mins.
  • Troubleshooting and Debug : 8mins.
  • Testing and CI/CD : 27mins.
  • Performance : 13mins.
  • Reliabiity : 19mins.
  • Testing and CI/CD : 27mins.
  • Flex Templates : 10mins.
  • Reliabiity : 19mins.
  • Summary : 4mins.
  • Flex Templates : 10mins.
  • Summary : 4mins.
See side-by-side differences in what you’ll learn

Description

In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.

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Serverless Data Processing with Dataflow: Operations
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