Mastering Azure Data Engineering: Part 3 – Azure Skills

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Mastering Azure Data Engineering: Part 3 – Azure Skills, Azure Data Mastery: Techniques & Best Practices for Data Factory, Synapse Analytics, DP-900, and DP-203.

Course Description

In this course, participants will delve into mastering Azure Data Engineering with a focus on honing essential Azure skills. This module, Part 3 of the series, specifically concentrates on Azure services vital for data engineering tasks. Through a combination of lectures, hands-on labs, and real-world case studies, learners will deepen their understanding of key Azure components such as Azure Storage and Azure SQL within the context of Azure Data Factory. The course empowers participants to streamline data workflows efficiently, optimizing data movement and manipulation processes. By the end of the course, students will have the expertise to leverage Azure Data Factory effectively for various data engineering tasks, from data ingestion to transformation and loading, enabling them to contribute significantly to data-driven initiatives within their organizations.

Course Objectives:

  1. Gain proficiency in utilizing Azure Storage within Azure Data Factory workflows.
  2. Develop skills in leveraging Azure SQL for data processing and manipulation within Azure Data Factory pipelines.
  3. Streamline data workflows effectively using Azure Data Factories, optimizing data movement and transformation processes.
  4. Acquire hands-on experience with copy data and delete activities in Azure Data Factory through practical case studies and exercises.

Target Audience:

  • Data Engineers
  • Data Analysts
  • Data Scientists
  • IT Professionals seeking to enhance their Azure data engineering skills

Prerequisites:

  • Basic understanding of Azure services and cloud computing concepts.
  • Familiarity with data engineering principles and practices.

Delivery Format:

  • Instructor-led training sessions
  • Hands-on labs and exercises
  • Real-world case studies

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