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Azure Data Factory For Data Engineers - Project on Covid19

Real world project for Data Engineers using Azure Data Factory, SQL, Data Lake, Databricks, HDInsight, CI/CD [DP203]

  1. Topics
  2. IT & Software
  3. Azure Data Factory

Azure Data Factory For Data Engineers - Project on Covid19

InstructorRamesh Retnasamy . 200,000+ Learners
Duration12h 42m
Students102.9K
Rating4.6 (17.9K)
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Price
$39.99
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Comidoc Analysis

End-to-end Azure Data Engineering via COVID-19 Datasets

Strengths

Comprehensive Pipeline Workflow

The curriculum covers a full lifecycle from environment setup and data ingestion to transformation using multiple modalities like Databricks and HDInsight, concluding with CI/CD via Azure DevOps.

Integrated Hands-on Practice

Instruction is reinforced through specific assignments within the transformation modules, helping to ground theoretical concepts in practical application.

Limitations

Service and Data Obsolescence

One signal from a review created before the displayed update suggests difficulties starting Databricks clusters on free subscriptions; while the course has an update label, it does not prove these service-specific issues were addressed. Another signal indicates a need for more recent data connection standards like Unity Catalog.

Instructional Nuance Gaps

A pre-update review notes that specific technical details, such as case sensitivity for code or potential dashboard delays after publishing, are not explicitly addressed in the instruction; the update label does not guarantee these nuances were incorporated.

Best suited to

  • Aspiring Azure Data Engineers
  • IT developers transitioning to cloud data roles
  • University students seeking project-sited portfolios

Less suited to

  • Learners requiring the most current Databricks Unity Catalog configurations
  • Those needing highly granular technical nuance regarding dashboard delays

Comidoc Score

7.1/10

Recommended
Defined audience

Comidoc verdict

Building end-to-end Azure data pipelines involves moving from resource setup to complex transformations and CI/CD workflows. By centering the instruction around a single, large-scale project, the curriculum demonstrates how different Azure services interact within a production-style environment.

The scope includes multiple transformation paths—including Databricks and HDInsight—and deployment strategies via Azure DevOps. However, some learners have encountered difficulties with service accessibility on free tiers, and there are indications that certain connection standards could be modernized to reflect current industry practices.

This course is best suited for beginners or those transitioning into data engineering who value a project-sited approach to understanding the Azure ecosystem.

Score breakdown

Curriculum depth
8.0

The curriculum covers diverse transformation methods including Data Flows, Databricks, and HDInsight, alongside CI/CD workflows.

Applied learning
8.0

The course is built around a central project with multiple embedded assignments for data transformation and pipeline creation.

Clarity & experience
6.5

One signal from a review created before the displayed update suggests that specific technical nuances, such as dashboard delays or case sensitivity, are not explicitly addressed; while the course has an update label, it does not prove these details were incorporated.

Currency & reliability
5.0

One signal from a review created before the displayed update suggests difficulties starting Databricks clusters on free subscriptions; while the course has an update label, it does not prove these service-specific issues were addressed.

Audience fit
6.5

The curriculum aligns with the goals of aspiring data engineers through its focus on Azure-specific tools and end-sprint pipelines.

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