Published 07/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 86 lectures (10h 50m) | Size: 4.2 GB
Comprehensive Data Factory Practical Hands-on Labs using REST API, SQL DB, On-Premise DB, VM, Data Lake, Blob[DP-203]
What you’ll learn
100% In depth Hands on Practical Lab Sessions
You will learn how to create Data driven, fully integrated, dynamic and automated production grade pipeline creation and orchestration
Real World Use Cases will detailed solutions
You will learn about Data Warehousing Concepts like Fact & dimension tables, SCD type1, type2, Incremental loading and implement using ADF
All the topics related to Azure Data Factory in DP 203, DP 900 certification are covered in this course.
You will learn how to connect to On Premise data stores, On premise SQL server via Self Hosted Integration Runtime and able to move On Premise data to cloud.
You will acquire good Data Engineering skills in Azure using Azure Data Factory (ADF), Azure Data Lake Gen2, Azure SQL Database, Azure Blob Storage and REST API
You will learn how to ingest data from sources such as REST API, Azure Blob Storage, SQL DB into Azure Data Lake Gen2 using Azure Data Factory (ADF)
You will learn how to transform data using Data Flows in Azure Data Factory (ADF) and load into Azure Data Lake Storage Gen2
You will learn extensively about Triggers in Azure Data Factory (ADF) and how to use them to schedule the data pipelines.
You will learn how to build production ready pipelines and good practices and naming standards
Requirements
Basic Database concepts
An Azure Account is required, If you don’t have one we will create a free account in the course
Description
Welcome to this amazing Azure Data Factory course. Below are key highlights of this course –
Fully Lab based Hands-on Course.
Course covers from basics to advanced concepts.
Real World Scenario based Interview Questions with detailed solution.
Real World Data Warehousing concepts like SCD type 1 & 2, Incremental load and complete Implementation using ADF.
Automated, Data-Driven, Dynamic Production grade Pipeline creation and Orchestration.
Covers most frequently used data sources such as Azure Blob, Azure Data Lake Gen2, Azure SQL DB, REST API, On Premise Database, On Premise Virtual Machines etc.
Covers Parameterized components and dynamic queries to build dynamic and flexible robust pipelines.
Covers all the important configurations and settings of different activities with practical demo.
Covers different types of Triggers, scheduling and their application in details. Trigger dependencies and pipeline chaining also covered.
Mapping Data Flows to create data transformation logics.
Debugging data flows, investigating issues, fixing failures etc .
Creating dependency between pipelines to orchestrate the data flow.
Building a solution architecture for a data engineering solution using Azure Data Engineering technologies such as Azure Data Factory (ADF), Azure Data Lake Gen2, Azure Blob Storage, Azure SQL Database, On Premise Database, On Premise Virtual Machines and RESTful API.
If you are planning for Azure Data Engineer certification[DP-900],[DP-203] then this course covers all concepts related to ADF.
Who this course is for
College / University Students looking for a career in Data Engineering
Freshers interested in Data Engineering on Microsoft Azure
Mid Level Data Engineering, Data Integration, ETL Developers
Data Engineers/ Data Warehouse Developers currently working on on-premises technologies, or other cloud platforms such as AWS or GCP who want to learn Azure Technologies
Professionals willing to do Microsoft Certifications such as DP-900, DP-203 etc
Mid Level Professionals who wants to learn Azure & Data Engineering
Experienced Professionals willing to master Azure Data Factory
Experienced Professionals willing to be Architect in order to understand capability of Data Factory
Data Scientists who want extend their knowledge into data engineering
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