Mastering Azure Data Engineering: Part 6 – Azure Skills

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Mastering Azure Data Engineering: Part 6 – Azure Skills, Azure Data Mastery: Techniques & Best Practices for Data Factory, Synapse Analytics, DP-900, and DP-203.

Course Description

Embark on an journey into Azure Data Engineering with a specialized focus on mastering key Azure skills. Part 6 of this comprehensive series delves into essential Azure services crucial for data engineering tasks. Through a blend of instructional sessions, hands-on labs, and practical case studies, participants will deepen their expertise in analyzing and transforming data using Spark within Azure Synapse Analytics. The course empowers learners to harness the power of Delta Lake in Azure Synapse Analytics for efficient data management and processing. By the conclusion of the course, students will be equipped with the knowledge and skills to leverage Spark and Delta Lake effectively, enhancing their capabilities in data engineering within the Azure ecosystem.

Course Objectives:

  1. Develop proficiency in analyzing data with Spark within Azure Synapse Analytics.
  2. Acquire skills in transforming data using Spark in Synapse Analytics, optimizing data processing workflows.
  3. Utilize Delta Lake in Azure Synapse Analytics for efficient data management and reliability.
  4. Apply learned concepts through hands-on exercises and real-world case studies, gaining practical experience in Spark and Delta Lake technologies.

Target Audience:

  • Data Engineers
  • Data Analysts
  • Data Scientists
  • IT Professionals seeking advanced Azure data engineering skills

Prerequisites:

  • Basic understanding of Azure services and cloud computing concepts.
  • Familiarity with data engineering principles and practices.
  • Prior experience with Spark or similar data processing frameworks is beneficial but not mandatory.

Delivery Format:

  • Instructor-led training sessions
  • Hands-on labs and exercises

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