Microsoft Azure Data Factory Course Overview

Microsoft Azure Data Factory Course Overview

The Microsoft Azure Data Factory course is designed to equip learners with a comprehensive understanding of data integration and workflows in the cloud. Through detailed lessons and hands-on labs, participants will delve into the world of data warehousing, exploring various components such as Azure SQL Database, Data Lake, and HDInsight. The course covers a wide range of topics, from planning and implementing data warehouse infrastructure to designing and managing data pipelines with Azure Data Factory (ADF).

Learners will gain practical skills in data movement and transformation, understanding how to secure data, implement disaster recovery strategies, and integrate with Azure Active Directory. They will also learn best practices for performance optimization and explore data migration tools. This curriculum is ideal for those seeking Azure ADF training, aiming to achieve Azure Data Factory certification, and looking to build a career in cloud data management. Upon completion, participants will be well-equipped to design, deploy, and manage data solutions using Azure Data Factory, making them valuable assets in the growing field of cloud data engineering.

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  • Live Online Training (Duration : 40 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

You can request classroom training in any city on any date by Requesting More Information

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Course Prerequisites

To successfully undertake training in the Microsoft Azure Data Factory course provided by Koenig Solutions, the following minimum prerequisites are recommended:

  • Basic understanding of database concepts, including relational databases and SQL (Structured Query Language).
  • Familiarity with data warehousing concepts and the purpose of a data warehouse.
  • Awareness of cloud computing fundamentals, particularly within the Microsoft Azure ecosystem.
  • Some experience with Microsoft Azure services, such as Azure SQL Database, Azure Data Lake, and Azure Active Directory, is beneficial.
  • Knowledge of ETL (Extract, Transform, Load) processes and the role they play in data integration.
  • A conceptual grasp of business intelligence and data analysis to appreciate the context in which Azure Data Factory is used.
  • Basic understanding of programming or scripting, which will be helpful when dealing with data transformation and pipeline creation.
  • Willingness to engage with hands-on labs and technical demonstrations to reinforce learning concepts.

Please note that while having a technical background is helpful, the course is designed to guide students through the fundamental and advanced concepts of Azure Data Factory. The course modules are structured to progressively build your knowledge and skills, regardless of your starting point.

Target Audience for Microsoft Azure Data Factory

The Microsoft Azure Data Factory course offers comprehensive training for IT professionals on cloud-based data integration and workflows.

  • Data Engineers
  • Cloud Solution Architects
  • Database Administrators
  • Business Intelligence Professionals
  • Data Warehouse Specialists
  • Data Analysts
  • IT Managers overseeing data management solutions
  • Developers looking to specialize in data warehousing on Azure
  • Technical Consultants involved in data-driven projects
  • DevOps Engineers focusing on data pipeline automation
  • Security Professionals managing data protection in the cloud
  • System Administrators transitioning to cloud-based data solutions

Learning Objectives - What you will Learn in this Microsoft Azure Data Factory?

Introduction to the Learning Outcomes of the Microsoft Azure Data Factory Course

This course equips learners with comprehensive skills in data warehousing, data integration, and data transformation using Microsoft Azure Data Factory and related Azure services.

Learning Objectives and Outcomes

  • Understand the core concepts of data warehousing and the considerations for implementing a data warehouse solution in Azure.
  • Deploy, manage, and optimize Azure SQL Databases, including securing data and disaster recovery options.
  • Plan and calculate the necessary compute and storage resources for a data warehouse infrastructure using Azure tools.
  • Design and implement a data warehouse with an emphasis on dimension and fact tables, as well as physical design.
  • Learn about columnstore indexes, their creation, and usage to enhance data warehouse performance.
  • Set up and manage Azure Data Factory, create pipelines, datasets, and integration runtimes for data processing.
  • Implement data copying, ingestion, and transformation with Azure Data Factory, ensuring data security and compliance.
  • Develop skills for using Azure Data Lake, HDInsight, and other tools for data ingestion, processing, and analytics.
  • Gain practical experience through labs and demonstrations on Azure Data Factory components, including linked services and activities.
  • Understand business intelligence concepts and how to consume data from a data warehouse for analysis and reporting.