Azure data factory Course with AWS GLUE (ETL)
Master ETL in cloud with AWS glue & Azure data factory lab
IT and Software ,IT Certifications,Amazon AWS
Lectures -83
Duration -9.5 hours
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Course Description
In this course, we would learn the following:
- We will start with the Basics of Serverless Computing.
- We will learn Schema Discovery, ETL, Scheduling, and Tools integration using Server AWS Glue Engine built on the Spark environment.
- We will learn to develop a centralized Data Catalogue too using Server AWS Glue Engine.
Businesses have always wanted to manage less infrastructure and more solutions. Big data challenges are continuously challenging the infrastructure boundaries. Having Server Storage, Server ETL, Server Analytics, and Server Reporting, all on one cloud platform sounded too good to be true for a very long time. But now it's a reality on the AWS platform. AWS is the only cloud provider that has all the native server-less components for a true server-less Data Lake Analytics solution.
This course understands your time is important, and so the course is designed to be laser-sharp on lecture timings, where all the trivial details are kept at a minimum and focus is kept on core content for experienced AWS Developers / Architects / Administrators. By the end of this course, you can feel assured and confident that you are future-proof for the next change and disruption sweeping the cloud industry.
I am very passionate about AWS Serverless computing on the Data and Analytics platform and am covering A-to-Z of all the topics discussed in this course.
This course will target anyone who likes to learn about Azure data factory and data bricks. This course will cover all ADF components from the Model and View layer. In this course, I have selected 15+ real-time industry-level project learning which will cover all the topics which is necessary to learn Azure data factory and data bricks and will be able to work on industry. This is a completely hands-on learning tutorial where we will do practical learning and by the end of this course we will develop a complete ADF application together (step by step) By the end of this course, you should be able to develop a complete ADF application by yourself.
If you are able to do practicals with me you will be able to get a complete picture of the data factory
I have also included lessons on the storage blob Storage, Amazon S3, Azure SQL Database etc. Also, there are lessons on Azure Data bricks. I have even included lessons on building reports using Power BI on the data processed by the Azure Data Factory data pipelines.
Who is this course for?
- Anyone who wants to learn and get hands-on Azure data factory and data bricks.
- Anyone looking for a job change in the data engineering field.
- Anyone who wants to learn AWS Serverless technologies for data and analytics should take this course.
Goals
Confidently work with AWS Serverless services to develop Data Catalogue, ETL, and Analytics on a Data Lake.
Build a serverless data lake on AWS using structured and unstructured data.
By the end of this course, you will be able to develop a pipeline in Azure data factory.
how to perform the transformation in Azure data factory.
you will learn how to develop an incremental load pipeline.
you will be able to understand about data bricks architecture and how to use.
Industry level SCD type-1,type-2 projects.
Failure handling and debug pipeline and learn about email alerts and all.
Prerequisites
Good to have Azure and AWS Accounts for the practical lab.
Good internet and laptop/desktop.
Willing to learn.

Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
1 Lectures
-
Introduction 00:48 00:48
DEMO PROJECT
2 Lectures

AWS GLUE
11 Lectures

AWS (ATHENA)
8 Lectures

ADF (COPY & DELETE activities)
8 Lectures

ADF ( SQL TO BLOB)
6 Lectures

ADF (CSV file to SQL table data pipeline)
3 Lectures

ADF (TRANSFORMATION)
7 Lectures

ADF (INCREMENTAL LOAD)
3 Lectures

ADF (Parameterization )
4 Lectures

ADF( SCD TYPE-1 & SCD TYPE 2)
6 Lectures

ADF (FAILURE)
2 Lectures

SQL
22 Lectures

Instructor Details

manish tiwari
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