Azure Data Factory V2: A Premium Practical Guide to Mas

Master Azure Data Factory, Azure Integration Tool, Azure Cloud ETL & ELT Tool, Microsoft Certification DP-200 & DP-201

Created by : Rated :4.7 59519 views

Last Updated: 2022-07-19 03:07:42 English Course Type: Self Learning

Student will learn how to utilize Azure Data Factory ,a cloud based integration service to design and develop different pipelines to move data from on premise to Azure Cloud and inter cloud sources.
One and only course on Udemy which covers best practices with respect to design performance oriented and efficient data movement pipelines and transformations using Azure Data Factory tool.
DP-200 Exam Topics: Implement the integration runtime for Data Factory, Implement Copy Activity within Azure Data Factory, Create linked services and datasets, Create pipelines and activities, Implement Mapping Data Flows in Azure Data Factory, Create and schedule triggers, Monitor Data Factory pipelines
This course is packed with different assignments and hand on practical to enable students get expertise in designing different pipelines to meet day to day need of a cloud data engineer.

In this course, students will learn how to use Azure Data Factory V2 (cloud based data integration service) to design data movement pipelines and transformation workloads. This course is a complete guide to data enthusiasts to understand each and every building blocks of Azure Data Factory. They will get practical exposure to use and implement different components of Azure Data Factory with basic overview of their settings and configuration. This course is enriched with best practices and recommended steps to design optimized data pipelines. After completing this course, one can easily design basic to medium complex level data movement pipelines with competency of using best practices and recommended techniques to build efficient data movement workloads. This course will enable students to qualify Microsoft Certification Exam DP 200 & DP 201 and make them capable of solving scenario based questions asked in these exams. This course covers industry level implementation and use cases.

Basic concept of data and data bases.
Requires laptop and internet connectivity.
Need to opt for Azure Trial Subscription (free of cost) to practice.

ETL Developer, Data Engineers, Data Architect, Data Integration Engineers and Cloud Enthusiasts

Section 1 : Introduction to Azure Data Factory 4 Lectures
Lecture 1 :
What is Azure Data Factory? Preview
Lecture 2 :
Provisioning Azure Data Factory V2 in Azure Portal
Lecture 3 :
Lab Spin-Up Azure Data Factory V2 in Azure Portal
Lecture 4 :
Check what You have Learnt
Test quiz on basic fundamentals we learned in this Section
Section 2 : Basic Entities and Building Blocks of Azure Data Factory V2 7 Lectures
Lecture 1 :
Basic Overview of ETL and ELT
Lecture 2 :
Azure Data Factory Building Blocks and Fundamental Entities
Lecture 3 :
What is Integration Runtime?
Lecture 4 :
Lab: Steps to Setup Integration Runtime
Lecture 5 :
Repository Integration in Azure Data Factory
Lecture 6 :
Lab : Walkthrough the Azure Data Factory Workspace
Lecture 7 :
Basic Overview of Data Integration Unit (DIU)
Section 3 : Practical & Theoretical Lesson on Control Flow Activities 16 Lectures
Lecture 1 :
Copy Data Activity
Lecture 2 :
Data Flow Activity
Lecture 3 :
Lookup Activity
Lecture 4 :
GET Metadata Activity
Lecture 5 :
Execute Pipeline Activity
Lecture 6 :
Execute SSIS Package Activity
Lecture 7 :
Stored Procedure Activity
Lecture 8 :
Validation Activity
Lecture 9 :
Wait Activity
Lecture 10 :
Web Activity
Lecture 11 :
Web Hook Activity
Lecture 12 :
For Each Activity
Lecture 13 :
If Condition Activity
Lecture 14 :
Switch Activity
Lecture 15 :
Until Activity
Lecture 16 :
Assignment for Control Flow Activities
Section 4 : Data Flow Transformation 8 Lectures
Lecture 1 :
Data Flow Introduction
Lecture 2 :
Data Flow Source And Sink
Lecture 3 :
How to spin your first Data Flow in Data Factory
Lecture 4 :
How to Execute Data Flow
Lecture 5 :
Sorting, Alter and Aggregation Transformation in Mapping Data Flow
Lecture 6 :
Derived Column Transformation
Lecture 7 :
JOIN Transformation
Lecture 8 :
Assignment
Section 5 : Trigger, Scheduling and Monitoring Pipelines 6 Lectures
Lecture 1 :
Monitoring Data Factory Pipelines
Lecture 2 :
Manage Data Factory Visually
Lecture 3 :
Triggers and Scheduling
Lecture 4 :
Lab: Create Triggers
Lecture 5 :
Lab: Monitor Pipeline Execution
Lecture 6 :
Lab: Create Alerts and Notifications
Section 6 : Best Practices in Azure Data Factory 5 Lectures 00:07:24
Lecture 1 :
Best Practices Part - 1
Lecture 2 :
Best Practices Part - 2
Lecture 3 :
Bulk Table Load (Concepts)
Lecture 4 :
Lab: Bulk SQL Table Load
Lecture 5 :
Incremental Load ( Walk Through)
Section 7 : Industry Use Cases and Real World Examples 1 Lectures
Lecture 1 :
Lab: Incremental Load

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Sujeet Singh,

59519 Course Views

1 Courses

- Microsoft Certified Solution Expert: Data Management and Analytics & Microsoft Certified Cloud Data Engineer - Expertise of working on cloud based technologies like Azure Synapse, Azure Data Factory and Azure Databricks. Experience of designing data solution in Azure Cloud to support Analytics and Business Intelligence need. - Experience of designing ELT and ETL solution and implementing Data Warehouse in cloud as well as on premise. - 8 + years of experience of working on Microsoft BI suite, Microsoft Azure and Big Data Ecosystems - Have worked on more than 5 enterprise level migration projects to migrate Big Data architectures from on premise to Big Data cloud platform. - Work as freelancer, consultant and trainer.