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What you'll learn?
- 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.
Course Overview
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.
Pre-requisites
- Basic concept of data and data bases.
- Requires laptop and internet connectivity.
- Need to opt for Azure Trial Subscription (free of cost) to practice.
Target Audience
- ETL Developer, Data Engineers, Data Architect, Data Integration Engineers and Cloud Enthusiasts
Curriculum 47 Lectures 00:07:24
-
Section 1 : Introduction to Azure Data Factory
- 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
-
Section 2 : Basic Entities and Building Blocks of Azure Data Factory V2
- 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
- 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
- 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
- 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
- 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
- Lecture 1 :
- Lab: Incremental Load
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Instructor
59090 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.
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