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Mastering Azure Data Engineering: Part 7 - Hands-On
Rating: 5.0 out of 5(2 ratings)
1,479 students

Mastering Azure Data Engineering: Part 7 - 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
English [Auto],

What you'll learn

  • 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 t
  • 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
  • Analyze data using Azure Synapse Analytics to derive insights and make informed business decisions.
  • Deploy and manage Microsoft Fabric for efficient data processing and resource optimization.

Course content

1 section • 6 lectures • 2h 6m total length

  • 28.Load data into a relational data warehouse31:11
  • 29.Analyze data in a lake database48:05
  • 30.Explore a relational data warehouse37:58
  • Exercise: Explore Azure Storage insight6:09
  • Exercise: Explore Spark Streaming in Azure Synapse Analytics in live streaming3:19
  • Follow this channel for updates: https://www.youtube.com/@MithrammaIT/playlists0:14

    Follow this channel for updates: https://www.youtube.com/@MithrammaIT/playlists

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

In this course module, participants will further their mastery of Azure Data Engineering by focusing on crucial Azure skills. Part 7 of the series concentrates on essential Azure services for efficient data management and analysis. Through a blend of comprehensive lectures, hands-on labs, and practical case studies, learners will deepen their understanding of loading data into relational data warehouses, analyzing data in lake databases, and exploring relational data warehouses using Azure tools. By the end of the course, students will possess the expertise to effectively manage and analyze data within Azure environments, empowering them to drive data-driven initiatives within their organizations.

Course Objectives:

  1. Acquire proficiency in loading data into relational data warehouses, optimizing data storage and retrieval processes.

  2. Develop skills in analyzing data stored in lake databases, utilizing Azure tools for efficient data exploration and analysis.

  3. Explore relational data warehouses effectively using Azure services, gaining insights and actionable intelligence from structured data sources.

Target Audience:

  • Data Engineers

  • Data Analysts

  • Data Scientists

  • IT Professionals seeking to enhance their Azure data management and analysis skills

Prerequisites:

  • Basic understanding of Azure services and cloud computing concepts.

  • Familiarity with data engineering and data analysis principles.

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.

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