Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Subscribe
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
Mastering Azure Data Engineering: Part 6 - Hands-On
Rating: 4.7 out of 5(3 ratings)
1,610 students

Mastering Azure Data Engineering: Part 6 - Hands-On

Azure Data Mastery: Techniques & Best Practices for Data Factory, Synapse Analytics, DP-900, and DP-203
Created byLakshmi Narayana Singilidevi
Last updated 6/2024
English

What you'll learn

  • Analyze and manipulate data using Apache Spark within Azure environments.
  • Implement data transformations leveraging Spark in Azure Synapse Analytics.
  • Utilize Delta Lake for managing big data workloads in Azure Synapse Analytics.
  • Apply real-time analytics techniques using Azure Stream Analytics and Microsoft Fabric.

Course content

1 section • 6 lectures • 1h 35m total length

  • 25. Analyze data with Spark32:31
  • 26. Transform data using Spark in Synapse Analytics23:44

    Transform data using Spark in Synapse Analytics shows loading CSV data, transforming it with Spark notebooks in a Synapse workspace, and saving partitioned results via Spark and SQL.

  • 27.Use Delta Lake in Azure Synapse Analytics31:52
  • Exercise: Explore Azure Stream Analytics using git clone3:40
  • Exercise: Explore Realtime Analytics in Microsoft Fabric in SaaS3:18
  • Follow this channel for updates: https://www.youtube.com/@MithrammaIT/playlists0:14

Requirements

  • To take this course, learners should have: 1. Basics of cloud concepts. 1. Familiarity with SQL for data querying and manipulation. 3. Access to an Azure free trial account for hands-on practice.

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

Who this course is for:

  • This course is designed for data engineers, data analysts, and IT professionals aiming to enhance their skills in Azure data engineering. It's also valuable for anyone interested in leveraging Azure services for data analytics and real-time processing. Whether you're a beginner looking to enter the field or an experienced professional seeking to expand your expertise, this course offers practical insights and hands-on experience to propel your career forward.

Report abuse