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    Data Engineering on Microsoft Azure: The Definitive Guide

    BY
    Udemy

    Develop a thorough understanding of the strategies and methodologies used for data engineering operations on the Microsoft Azure platform.

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    Mode

    Online

    Fees

    ₹ 599 3699

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based

    Course overview

    Azure data engineers incorporate, modify, and strengthen data from various structured and unstructured data system applications into structures suitable for constructing analytics solutions. Wadson Guimatsa - Data Engineer created the Data Engineering on Microsoft Azure: The Definitive Guide certification course, which is presented by Udemy and is intended for individuals who want to learn how to design data models, create data pipelines, and navigate large datasets on the Azure platform.

    Data Engineering on Microsoft Azure: The Definitive Guide online course contains 12 hours of video-based lessons along with 23 downloadable study materials and 4 articles that focus on assisting individuals in the development of data warehouses, data lakes, and lakehouse architecture. Data Engineering on Microsoft Azure: The Definitive Guide online classes cover topics such as relational databases, data transformation, data analysis, and database query, as well as how to create a contemporary data and analytics platform using the extensive features of Azure data services.

    The highlights

    • Certificate of completion
    • Self-paced course
    • 12 hours of pre-recorded video content
    • 4 articles 
    • 23 downloadable resources

    Program offerings

    • Online course
    • Learning resources
    • 30-day money-back guarantee
    • Unlimited access
    • Accessible on mobile devices and tv

    Course and certificate fees

    Fees information
    ₹ 599  ₹3,699
    certificate availability

    Yes

    certificate providing authority

    Udemy

    What you will learn

    Database knowledge Knowledge of apache spark

    After completing the Data Engineering on Microsoft Azure: The Definitive Guide online certification, individuals will be introduced to the fundamentals of data engineering using the features of Microsoft Azure and will acquire a solid understanding of the techniques to use tools like Azure data studio or SQL server management studio to connect Azure SQL databases. In this data engineering course, individuals will explore the functionalities of various tools including Azure key vault, Azure SQL, Azure Synapse, Azure blob storage, Azure CLI, T-SQL, and Apache Spark. In this data engineering certification, individuals will learn about strategies to work with unstructured data, semi-structured data, data flows, ETL pipelines, relational databases, shared access signatures, database querying, data analysis, data transformation, and more.

    The syllabus

    Introduction - Understanding Core Data Concepts

    • Introduction
    • What is Data - A simple definition
    • What is Structured Data
    • What is Non Relational Data
    • What is Data Ingestion
    • What is Data Processing
    • Batch Processing vs Stream Processing
    • What is Data Analytics

    Azure SQL - Introduction

    • Create a Single Instance Database
    • What is a Resource Group
    • Azure Data Studio - Introduction
    • Create a Virtual Machine
    • Connect to Azure Database from an Azure Virtual Machine
    • Authentication and Authorization
    • Create a SQL Login and User
    • SQL Server Management Studion - Introduction
    • Understanding Tables and Views
    • How to Create a Database Diagram in SSMS
    • Azure Cost Management - How to Create a Budget in Azure

    Azure Blob Storage - Introduction

    • Introduction to Azure Storage
    • Create an Azure Storage Account
    • Upload Data using the Azure Portal
    • Upload Data using Azure Storage Explorer
    • Connect a Storage Account with a Shared Access Signature
    • Azure CLI - Generate a Shared Access Signature
    • Understanding Data Redundancy
    • Azure Storage Account - Redundancy Options

    Azure Data Factory - Core Concepts

    • Section Intro
    • Create Data Store and Target
    • Create Data Factory and Linked Services
    • Create Datasets
    • Create Pipeline and Activities
    • Create Mapping Data Flow and Adding Sources
    • Mapping Data Flow - Joining Sources
    • Mapping Data Flow - Aggregate Data
    • Mapping Data Flow Execution
    • Mapping Data Flow and Apache Spark Execution

    Practice Section: Build an ETL Pipeline with Azure Data Factory

    • Introduction
    • Cost Warning - Data Pipeline Pricing
    • IMPORTANT Download Resources Before Starting
    • Azure SQL - Contained Users
    • Azure Key Vault - Store SQL Server Secrets
    • Azure Key Vault - Linked Service
    • Create Azure Storage Account
    • Azure Managed Identity - Create a Linked Service To Azure Blob Storage
    • Azure Role Based Access Control - Grant Access To Managed Identity
    • Create a Dataset for the Lookup Activity
    • Azure Data Factory - Lookup Activity
    • Azure Data Factory - ForEach Activity & Pipeline Expressions
    • Azure Data Factory - ForEach Activity - Part II
    • Parameterize a Dataset Part I - Container Name
    • Parameterize a Dataset Part II - Directory Name
    • Parameterize a Dataset Part III - File Name
    • Mapping Data Flow - JSON Source
    • Mapping Data Flow - Parquet Source
    • Mapping Data Flow - JOIN & Derived Column Transformations
    • Mapping Data Flow - Aggregate Transformation
    • Mapping Data Flow - Parameterized CSV File Sink
    • Azure Data Factory - Store SAS In Azure Key Vault
    • Azure Data Factory - Copy Activity Merge Behavior
    • Azure Data Factory - End To End Pipeline Execution
    • Azure Data Factory - Storage Event Triggers

    Azure Synapse Analytics - Serverless SQL pool

    • Important Download Resources Before Starting
    • Data Processing - OLAP vs OLTP
    • Azure Synapse Analytics - Create a Synapse workspace
    • Azure Synapse Analytics - Serverless SQL Pool Introduction
    • Serverless SQL pool - Connect with Azure AD User & Azure Data Studio
    • Serverless SQL pool - Server Level Credential
    • Openrowset - Read Parquet Files
    • Openrowset - Read CSV Files
    • Openrowset - Read JSON - Line Delimited JSON
    • Openrowset - Read JSON - Array of Objects
    • Serverless SQL pool - Introduction to External Tables
    • Serverless SQL pool - Create External Table - Part I
    • Serverless SQL pool - Create External Table - Part II
    • Serverless SQL pool - Create External Table III - How to Handle Dirty Records
    • Serverless SQL pool - CETAS - Create External Table As Select

    Azure Synapse Analytics - Serverless Apache Spark pool

    • Apache Spark - Architecture
    • Create a Serverless Apache Spark Pool
    • Create and Run a Spark Notebooks
    • Scaling a Serverless Apache Spark Pool
    • Azure Synapse Analytics - Workspace Quotas
    • Working with Azure Data Lake Storage
    • Working with Azure Blob Storage
    • Working with Azure SQL
    • Practice - Configure your favorite IDE tool

    Instructors

    Mr Wadson Guimatsa
    Data Engineer
    Freelancer

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