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Azure Data Engineering Full Stack Course Details
 

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Batch Date: Feb 28th @10:30AM

Faculty: Mr. Sameer (10+ Yrs of Exp,.. & Real Time Expert)

(Leading Faculty in Twin Cities)

Duration : 3 Months

Venue :
DURGA SOFTWARE SOLUTIONS,
Flat No : 202, 2nd Floor,
HUDA Maitrivanam,
Ameerpet, Hyderabad - 500038

Ph.No: +91 - 9246212143, 80 96 96 96 96

Syllabus:

Azure Data Engineering

Module 1: Cloud Computing Concepts

  • What is the "Cloud" ?
  • Why Cloud Services
  • Types of Cloud Models
    • Deployment Models
      • Private Cloud
      • Public Cloud
      • Hybrid cloud
  • Types of Cloud Services
    • Infrastructure as a Service(IaaS)
    • Platform as a Service(PaaS)
    • Software as a Service(SaaS)
  • Comparing Cloud Platforms
    • Microsoft Azure,
    • Amazon Web Services,
    • Google Cloud Platform
  • Characteristics of Cloud Computing
    • On-demand self-service
    • Broad network access
    • Multi-tenancy and resource pooling
    • Rapid elasticity and scalability
    • Measured service
  • Cloud Data Warehouse Architecture
    • Shared Memory architecture
    • Shared Disk architecture
    • Shared Nothing architecture

Module 2: BigData Introduction

  • What is BigData?
  • BigData Sources
  • Data vs Information
  • Characteristics of BigData
    • Variety
    • Velocity
    • Volume
    • Veracity
    • Value
  • Types Of BigData
    • Structured Data
    • Unstructured Data
    • Semi Structured Data

Module 3: Dimensional Modelling

  • OLTP System
    • Relational Modelling
  • Characteristics Features of OLTP
  • Enterprise Data Warehouse
    • Dimensional Modelling
  • Dimensional Modelling-Schemas
    • Star Schema
    • Snowflake Schema
    • Multi Star Schema
  • Dimensional Tables
  • Fact Tables
  • Types of slowly Changing Dimensions
    • Type1 Dimension
    • Type2 Dimension
    • Type3 Dimension
  • Types Facts
    • Additive Facts
    • Semi Additive Facts
    • Non-Additive Facts

Module 4: Azure SQL Database

  • Introduction Azure SQL Database.
  • Comparing Single Database
  • Managed Instance
  • Creating and Using SQL Server
  • Creating SQL Database Services.
  • Azure SQL Database Tools.
  • Migrating on premise database to SQL Azure.
  • Purchasing Models
  • DTU service tiers
  • vCore based Model
  • Serverless compute tier
  • Service Tiers
    • General purpose / Standard
    • Business Critical / Premium
    • Hyper scale
  • Deployment of an Azure SQL Database
  • Elastic Pools.
  • What is SQL elastic pools
    • Choosing the correct pool size
  • Creating a New Pool
  • Manage Pools

Module 5: Azure Storage Service

  • Azure Storage Account
  • Features of Azure storage Service
  • Introduction to Blob Storage Service
  • Blob Storage Architecture
  • Blob Storage Features
  • Types of Blobs
    • Block Blobs
    • Append Blobs
    • Page Blobs
  • Creating a Storage Account
  • Azure Storage Performance Tiers
    • Standard
    • Premium Performance
  • Understanding Data Replication
    • LRS ( Locally Redundant Storage)
    • ZRS (Zone Redundant Storage)
    • GRS (Geo Redundant Storage)
  • Azure Storage-Access Tiers
    • Hot
    • Cold
    • Archive
  • Working with Containers and Blobs
  • Soft Delete
  • Azure Storage Explorer
  • Access blobs securely
  • Access Key
  • Account Shared Access Token
  • Service Shared Access Token
  • Azure Maximum Scalability Or Limits

Module 6: Azure Data Lake Storage Services

  • Introduction to Azure Data Lake
  • What is Data Lake?
  • What is Azure Data Lake?
  • Data Lake Architecture?
  • Working with Azure Data Lake Storage Gen1
  • Features of Data Lake Storage Gen1
  • Understanding Azure Data Lake Gen2
  • Features of Data Lake Storage Gen2
  • Differences Between Gen1 & Gen2 Storage
  • Explore Data Lake Storages
  • Prevising Data Lake Storage Gen1 Service
  • Provising Data Lake Storage Gen2 Service
  • Uploading Sample File
  • Using Azure Portal
  • Using Storage Explorer

Azure Data Factory:

Module 7: Azure Data Factory Introduction

  • What is Azure Data Factory (ADF)?
  • Azure Data Factory Key Components
    • Pipeline
    • Activity
    • Linked Service
    • Data Set
    • Integration Runtime
    • Triggers
    • Data Flows
  • Create Resource Group
  • Create Storage Account
  • Creation of Azure Data Factory Service

Module 8: Working with Copy Activity

  • Understanding Azure Data Factory UI
  • Copy Data from Blob Storage Service to Azure SQL Database
  • Copy data from file storage account to file storage account
  • Create Linked service for various data stores and compute
  • Creation of Datasets that points to file and table
  • Design Pipelines with various activities
  • Create SQL Server on Virtual Machines( On-Premise)
  • Define Copy activity and it features
  • Copy Activity-Copy Behavior
  • Copy Activity Data Integration Units
  • Copy Activity- User Properties
  • Copy Activity- Number of parallel copies
  • Working with Lookup Activity
  • Understanding of Each Activity
  • Filter Activity
  • Get Metadata Activity
  • Lift and Shift
  • Hosting Azure - SSIS Integration Runtime
  • Execute SSIS Packages from ADF
  • Monitoring Pipeline
  • Debug Pipeline
  • Trigger pipeline manually
  • Monitor pipeline
  • Trigger pipeline on schedule

Module 9: Practical Scenarios and Use Cases

  • ADF_PracticeSession1_Blob_To_Blob
  • ADF_PracticeSession2_CopyActivity_Prefix_Wildcard_FilePath_Blob_To_Blob
  • ADF_PracticeSession3_Blob_To_Azure_SQLDB
  • ADF_PracticeSession4_Blob_To_Azure_SQLDB
  • ADF_PracticeSession5_Dataset_Parameters_Blob_To_Azure_SQLDB
  • ADF_PracticeSession6_Blob_To_ADLS_Gen2
  • ADF_PracticeSession7_ADLS_Gen1_To_ADLS_Gen2
  • ADF_PracticeSession8_Pipeline_Dataset_LinkedService_Parameters
  • ADF_PracticeSession9_FilteringFileFormats_Getmetadata_Filter_ForEach_Copy_Activity
  • ADF_PracticeSession10_FilteringFileFormats_Getmetadata_Filter_ForEach_Copy_Activity
  • ADF_PracticeSession11_BulkCopy_Tables_Files
  • ADF_PracticeSession12_Container_Parameterization_Blob_To_Blob_Storage
  • ADF_PracticeSession13_ExecuteCopyActivity_BasedOnFileCount
  • ADF_PracticeSession14_StoredProcedures_Parameters
  • ADF_PracticeSession15_CopyActivity_CustomSQL_Queries_StoredProcedures
  • ADF_PracticeSession16_Pipeline_Audit_Log
  • ADF_PracticeSession17_Copybehaviour
  • ADF_PracticeSession18_CSV_To_JSON_Format
  • ADF_PracticeSession19_Copy_JSON_File_To_AzureSQL
  • ADF_PracticeSession20_Add_AdditionalColumns_WhileCopyingData
  • ADF_PracticeSession21_CopyDataTool
  • ADF_PracticeSession22_Custom_Email_Notification
  • ADF_PracticeSession23_AzureKeyVault_Integration
  • ADF_PracticeSession24_Incremental_Load
  • ADF_PracticeSession25_Integration_Runtime
  • ADF_PracticeSession26_On-Premise_SQLServer_ADLS_Gen2
  • ADF_PracticeSession27_On-Premise_FileSystem_ADLS_Gen2
  • ADF_PracticeSession28_REST_API_Integration
  • ADF_PracticeSession29_CosmosDB_Introduction
  • ADF_PracticeSession30_Eventbased_Trigger
  • ADF_PracticeSession31_Scheduled_Trigger
  • ADF_PracticeSession32_TumblingWindow_Trigger
  • ADF_PracticeSession33_Blob_SQLDB_Executepipeline_Activity
  • ADF_PracticeSession34_SQLDB_BLOB_Overwrite_Append_Mode
  • ADF_PracticeSession36_Dataflows_Introduction
  • ADF_PracticeSession37_Dataflows_Select_Filter_DerivedColumn_Transformation
  • ADF_PracticeSession38_Dataflows_Select__DerivedColumn_Aggregator_Sort_Transformation
  • ADF_PracticeSession39_Dataflows_ConditionalSplit_Transformation
  • ADF_PracticeSession40_Dataflows_Join_Transformation
  • ADF_PracticeSession41_Dataflows_Union_Transformation
  • ADF_PracticeSession42_Dataflows_Lookup_Transformation
  • ADF_PracticeSession43_Dataflows_Exists_Transformation
  • ADF_PracticeSession44_Dataflows_Rank_Transformation
  • ADF_PracticeSession45_Dataflows_Pivot_Transformation
  • ADF_PracticeSession46_Dataflows_UnPivot_Transformation
  • ADF_PracticeSession47_Dataflows_SurrogateKey_Transformation
  • ADF_PracticeSession48_Dataflows_AlterRow_Transformation
  • ADF_PracticeSession49_Remove Duplicate rows using data flows
  • ADF_PracticeSession50_Slowly Changing Dimension Type1 (SCD1) with Hash Key Function

Module 10: Assignments & Case Studies

  • ADF_Azure_HDInsight Integration
  • ADF_Azure_HDInsight with Spark Cluster
  • ADF_Azure_Databricks Integration

Azure Databricks:

Module 11: Introduction to Azure Databricks

  • Introduction to Databricks
  • Azure Databricks Architecture
  • Azure Databricks Main Concepts

Module 12: Databricks Integration with Azure Blob Storage

  • Read data from Blob Storage and Creating Blob mount point

Module 13: Databricks Integration with Azure Data Lake Storage Gen2

  • Reading files from Azure Data Lake Storage Gen2

Azure Synapse Analytics:

Module 14: Introduction to Azure Synapse

  • Technical requirements
  • Interdiction the components of Azure synapse
  • Creating synapse Workspace
  • Understanding Azure Data Lake Exploring Synapse Studio

Module 15: Consideration for Your Compute Environment

Technical requirements Introducing SQL Pool

  • Creating SQL Pool
  • Understanding Synapse SQL Pool
  • Architecture and component
  • Examining DWUs
  • Understanding distribution in Synapse SQL Pool
  • Understanding portions in Synapse SQL Pool
  • Using temporary table in Synapse SQL Pool
  • Discovering the benefits of Synapse SQL Pool

Understanding Synapse SQL on demand

  • SQL on-demand architecture and components
  • Learning about the benefits of Synapse SQL on-demand

Module 16: Bringing Your Data to Azure Synapse

  • Technical requirements
  • Using Synapse pipelines to import data
  • Bringing data to your Synapse SQL Pool using Copy Data tool
  • Using Azure Data Factory to import data
  • Using SQL Server integration Services to import data

Module 17: Using Synapse Pipelines to Orchestrate Your Data

  • Technical requirements
  • Introducing synapse pipe lines
    • Integration runtime
    • Activities
    • Pipelines
    • Triggers
  • Creating linked services
  • Defining source and target
  • Using various activities in synapse pipelines
  • Scheduling synapse pipelines
  • Creating pipelines using samples