Azure Data Engineer Technologies for Beginners [DP-200, 201]

Azure Data Engineer Technologies for Beginners [DP-200, 201] | Udemy
English | Size: 11.06 GB
Genre: eLearning

What you’ll learn
You will be able to identify right Azure SQL Server deployment option, purchasing model and service tier according to requirements and will be able to deploy it in cloud.
You will able to deploy Azure Synapse Analytics (formerly known as Azure SQL Data warehouse) in Azure Cloud environment.
You will have good internal MPP architecture understanding, and so you will be able to analyse your on-premises data warehouse, and migrate data to Azure Data Warehouse.
You will be able to create Azure Data Lake Gen1 storage account, populate it will data and analyze it using U-SQL Language.
You will understand Azure Data Factory key components and advantages. You will be able to create, schedule and monitor simple pipelines.
We will understand how HDInsight makes Hadoop easy, and we will go through simple demo where we’ll fetch data from Data Lake, process it through Hive and later will store data in SQL Server.

By the end of this course

Microsoft Azure SQL Server –

You will know the advantages of Azure Database over on-premises Database

You will be able to provision all three types of Azure Database PaaS Deployments (Single, Elastic Pool, Managed Instance)

You will learn different purchasing models and Service tiers and how to configure them according to requirements.

You will be able to provision Azure Database in Virtual Machine (IaaS)

You will be able to deploy Elastic Pool Database and able to add/remove more databases from the pool.

You will be able to deploy the Managed Instance Database, configure it and connect it with your SQL Server Management studio.

Microsoft Azure Synapse Analytics Service

You will learn why we should consider warehousing solutions in the cloud.

You will learn about Microsoft’s brand new Azure Synapse analytics service, and how this service brings together enterprise data warehousing and Big Data analytics, and provide a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

You will learn the difference between Traditional vs Modern vs Synapse Architecture.

You will learn Azure famous MPP (Massive Parallel Processing) architecture

You will also learn many internal concepts like Data Distribution, Sharding, and partitioning.

You will learn different migration methods and best practices.

You will learn PolyBase setup (Best Loading method)

You will perform a lot of demos to migrate data to Azure SQL Data warehouse using SSIS, Data Factory and PolyBase.

Microsoft Azure Data Lake Gen1

You will learn the limitations of traditional database systems to handle the Big Data revolution.

You will learn the difference between Azure Data Lake, SSIS, Hadoop and Data Warehouse.

You will be able to create Azure Data Lake Gen1 storage account, populate it will data and analyze it using U-SQL Language.

Microsoft Azure Data Factory –

You will understand Azure Data Factory’s key components and advantages.

You will be able to create, schedule and monitor simple pipelines.

Hadoop Basics

You will learn a fundamental understanding of the Hadoop Ecosystem and 3 main building blocks.

This module will prepare you to start learning Big Data in Azure Cloud using HDInsight.

Microsoft HDInsight –

You will learn what are the challenges with Hadoop and how HDInsight solves these challenges.

You will also learn Cluster types, HDInsight Architecture and other important aspects of Azure HDInsight.

You will also go through demo where we’ll fetch data from Data Lake, process it through Hive and later will store data in SQL Server.

Who this course is for:
Beginners in Azure Platform
Database Developer
Database Administrators (DBA)
Business Intelligence (BI) Developers
Data Engineers
Data Scientist
Data Analyst or similar profiles
Other on-premises Database related profiles who want to learn how to implement these technologies in Azure Cloud.
Anyone who is looking forward to start his career as a Azure Data Engineer

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