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Azure Data Factory Essentials Training
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 56 lectures (3h 36m) | Size: 1.05 GB

Introduction to Azure Data Factory.


Learn How to Build a Complete ETL Solution in Azure Data Factory & How to Integrate Pipelines with Azure Databricks

You will understand how it can be used to integrate many other technologies with an ever-growing list of connectors.

How to set up a Data Factory from scratch using the Azure Portal and PowerShell.

Activities and Components that makeup Data Factory. It will include Pipelines, Datasets, Triggers, Linked Services, and more.

How to transform, ingest, and integrate data code-free using Mapping Data Flows.

How to integrate Azure Data Factory and Databricks. We'll cover how to authenticate and run a few notebooks from within ADF.

Azure Data Factory Deployment using Azure DevOps for continuous integration and continuous deployment (D)

No previous experience with Data Factory is required, we will work our way through step by step

TL;DR.

This course will introduce Azure Data Factory and how it can help in the batch processing of data. Students will learn with hands-on activities, quizzes, and a project, how Data Factory can be used to integrate many other technologies together to build a complete ETL solution, including a D pipeline in Azure DevOps. Some topics related to Data Factory required for the exam DP-203: Data Eeering on Microsoft Azure, are covered in this course.

Learn by Doing

Together, you and I are going to learn everything you need to know about using Microsoft Azure Data Factory. This course will prepare you with hands-on learning activities, videos, and quizzes to help you gain knowledge and practical experience as we go along.

At the end of this course, students will have the opportunity to submit a project that will help them to understand how ADF works, what are the components, and how to integrate ADF and Databricks.

Student key takeaways:

The student should understand how ADF orchestrates the features of other technologies to transform or analyze data.

The student should be able to explain and use the components that make up ADF.

The student should be able to integrate two or more technologies using ADF.

The student should be able to confidently create medium complex data-driven pipelines

The student should be able to develop a D pipeline in Azure DevOps to deploy Data Factory pipelines

What You'll Learn:

You will understand how it can be used to integrate many other technologies with an ever-growing list of connectors.

How to set up a Data Factory from scratch using the Azure Portal and PowerShell.

Activities and Components that makeup Data Factory. It will include Pipelines, Datasets, Triggers, Linked Services, and more.

How to transform, ingest, and integrate data code-free using Mapping Data Flows.

How to integrate Azure Data Factory and Databricks. We'll cover how to authenticate and run a few notebooks from within ADF.

Azure Data Factory Deployment using Azure DevOps for continuous integration and continuous deployment (D)

Data Factory Essentials Training - Outline

Introduction

Modules introduction

Getting Started

Understand Azure Data Factory Components

Ingesting and Transfog Data with Azure Data Factory

Integrate Azure Data Factory with Databricks

Continuous Integration and Continuous Delivery (D) for Azure Data Factory

Getting started

Sign up for your Azure free account

Setting up a Budget

How to set up Azure Data Factory

Azure Portal

PowerShell

Azure Data Factory Components

Linked Services

Pipelines

Datasets

Data Factory Activities

Parameters

Pipeline Parameters

Activity Parameters

Global Parameters

Triggers

Integration Runs (IR)

Azure IR

Self-hosted IR

Linked Self-Hosted IR

Azure-SSIS IR

Quiz

Ingesting and Transfog Data

Ingesting Data using Copy Activity into Data Lake Store Gen2

How to Copy Parquet Files from AWS S3 to Azure SQL Database

Creating ADF Linked Service for Azure SQL Database

How to Grant Permissions on Azure SQL DB to Data Factory Managed Identity

Ingesting Parquet File from S3 into Azure SQL Database

Copy Parquet Files from AWS S3 into Data Lake and Azure SQL Database (intro)

Copy Parquet Files from AWS S3 into Data Lake and Azure SQL Database

Monitoring ADF Pipeline Execution

Transfog data with Mapping Data Flow

Mapping Data Flow Walk-through

Identify transformations in Mapping Data Flow

Multiple Inputs/Outputs

Schema Modifier

Formatters

Row Modifier

Destination

Adding source to a Mapping Data Flow

Defining Source Type; Dataset vs Inline

Defining Source Options

Spinning Up Data Flow Spark Cluster

Defining Data Source Input Type

Defining Data Schema

Optimizing Loads with Partitions

Data Preview from Source Transformation

How to add a Sink to a Mapping Data Flow

How to Execute a Mapping Data Flow

Quiz

Integrate Azure Data Factory with Databricks

Project Walk-through

How to Create Azure Databricks and Import Notebooks

How to Transfer Data Using Databricks and Data Factory

Validating Data Transfer in Databricks and Data Factory

How to Use ADF to Orchestrate Data Transformation Using a Databricks Notebook

Quiz

Continuous Integration and Continuous Delivery (D) for Azure Data Factory

How to Create an Azure DevOps Organization and Project

How to Create a Git Repository in Azure DevOps

How to Link Data Factory to Azure DevOps Repository

How to version Azure Data Factory with Branches

Data Factory Release Workflow

Meg Data Factory Code to Collaboration Branch

How to Create a D pipeline for Data Factory in Azure DevOps

How to Create a CICD pipeline for Data Factory in Azure DevOps

How to Execute a Release Pipeline in Azure DevOps for ADF

Quiz

Data Professionals

Data Architects

Data Eeers

ETL Developers

Software Developers




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