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Azure Certification BootCamp for Exam 70-475 (Big Data Analytics Solutions)


Duration: 4 Days


Cloud is being leveraged for all the Data Science operations worldwide. It is becoming an intrinsic part of the overall eco system of digital or smart solutions. This hands-on course is designed to get knowledge to be able to clear the 70-475: Designing and Implementing Big Data Analytics Solutions Exam. This hands-on course focuses on designing and implementing Big Data solutions on Microsoft Azure Cloud by using various services like Azure Event Hub, Azure HDInsight, Azure Data Factory and many more. As a participant, you will learn how to design and build Lambda Architecture for any Data Science operation right from ingestion of data to dashboarding the data. The focus will be majorly on utilizing Azure services. We would also discuss features such as Data Security and Automation in Cloud. We will spend about half the time in this course doing hands-on labs using our custom curriculum....Read more


  • To attain a comprehensive understanding of Cloud Data Platform Solutions
  • Understanding integration of various components for Data Processing and Analysis
  • Create Lambda Architecture for smart solutions
  • Learn how to design data solutions and implement with different architecture patterns

Who Should Attend

  • Data Science Professionals who want to enhance their existing data engineering skills to build Lambda Architecture with Microsoft Azure Cloud and Hybrid Solutions
  • Data Platform Architects, Data Engineers and Data Scientists who want to get hands-on experience on Cloud Data Platform Solutions
  • Professionals who want to jump start their career in Cloud Data Platform
  • Candidates looking to get certified on 70-475: Designing and Implementing Big Data Analytics Solutions Exam


  • Fundamental knowledge of Cloud Computing
  • Basic understanding of Big Data
  • Some experience with Data Science

Course Outline

Day 1

  1. Azure Fundamentals
    • Introduction to Azure
    • Different Segments SaaS, PaaS, and IaaS
    • Azure Regions and Data Centers
    • Overview of all Azure Services
    • Azure Portals
  2. Introduction to Data Science Technology Stack
    • Introduction to Data Science
    • Overview of the Data Science Process
    • Introduction to Data Science Technologies
    • Introduction to Machine Learning
    • Fundamentals of Big Data
    • Fundamentals of Machine Learning
    • Fundamentals of Data Warehousing
    • Fundamentals of Cognitive Intelligence
  3. Introduction to IoT
    • Fundamentals of IoT
    • Co-relationship of IoT and Data Science
    • Use Cases of IoT

Day 2

    1. Azure Storage
      • Understanding Storage Account
      • Features
      • Storage Account Replication Techniques: LRS, ZRS, GRS & RA-GRS
      • Protocols
      • Consistency Model
    2. Azure File Storage
      • Use cases for Azure File Storage
      • Share, Files and Folders
      • Access Control
    3. Azure Blob Storage
      • Use Cases for Azure Blob Storage
      • Containers
      • Block Blob
      • Page Blob
      • Access Control
      • Shared Access Signatures
      • Locking Operations
    4. Azure Table Storage
      • Brief intro to NoSQL
      • Use Cases for Azure Table Storage
      • Schema for Azure Tables
      • Scaling Tables
      • Access Control
    5. Azure Queue Storage
      • Need for Queues
      • Understanding Azure Queues

Lab: Microsoft Azure Storage Lab; Using File storage, Blog storage, and Table Storage

    1. Azure Virtual Machines
      • Understanding VMs Architecture
      • Types of OS supported Images by Azure
      • Virtual Machine instances
        • Virtual Machine Types
        • Compute Tiers
        • Instance Types
      • Pricing
      • Understanding OS Disk and Data Disk
      • Understanding Custom Image
      • Types of Provisioning
      • Disks & Images
      • Virtual Machine Management, Automation and Scripting
      • Cloud Service
      • Endpoints
      • Load Balanced Endpoint
      • Azure Virtual Machines for Data Science

Lab: Launching and Accessing Azure Virtual Machines

Day 3

    1. Getting started with HDInsight
      • HDInsight as a Cloud Service
      • Azure HDInsight Hadoop Cluster
      • Azure HDInsight Spark Cluster
      • Azure HDInsight Storm Cluster
      • Azure HDInsight HBase Cluster
      • Azure HDInsight R Server Cluster
      • Azure HDInsight Kafka Cluster
      • Creating HDInsight Cluster
      • Managing HDInsight Cluster with Portal
      • Accessing and Managing HDInsight Name Node
      • Configuring and Deploying HDInsight Emulator

Lab: Finding Most Visited Wiki Pages MapReduce job using HDInsight Emulator

    1. Data Lake Store for Big Data Scenarios
      • Concept of Data Lake store
      • Configuring Data Lake store using Azure Portal and PowerShell
      • Overview of Data Lake Security
      • Data Lake Store integration with Azure Services
      • Azure Blob Storage vs Azure Data Lake Store
      • Integration with Azure Services

Lab: Provisioning HDInsight Cluster with Data Lake store

    1. Azure Event Hub
      • Introduction to Data Integration
      • Advantages of Azure Event Lab
      • Information Ingestion Process
      • Partitions
      • Publishers and Subscribers Overview
      • AMQP vs HTTPS
      • Stream Offset
      • Check-Pointing
      • Throughput
      • Input Sources
      • Apache Kafka vs Azure Event Hubs
    2. Azure Stream Analytics
      • Overview of Azure Stream Analytics as a service
      • Components of Azure Stream Analytics
      • Integration with Other Services for Input / Output
      • Windows Functions
      • Query Types
      • Scaling Azure Stream Analytics
      • Use Cases
      • Azure Stream Analytics vs Apache Storm

Lab: Creating and Integrating Azure Event Hub and Azure Stream Analytics

Day 4

    1. Azure Data Factory
      • Introduction
      • Key Concepts
      • Activities
      • Data Movement
      • Data Transformation
      • Pipelines
      • Datasets
      • Linked Services
      • Supported Data Sources and Sinks
      • PowerShell for Azure Data Factory

Lab: Creating an Azure Data Factory pipeline with copy activity to move data from Azure Blob storage to Azure SQL Dtabase

    1. Power BI
      • Introduction to Power BI
      • Why to use Power BI
      • Tools with Power BI
      • Service Integration
      • Power BI Components
      • Use Cases

Lab: Data analysis with PowerBI using Azure Data Lake Store

  1. Azure Automation
    • Automation Account
    • Runbook
    • Scheduled Jobs
    • Use Case for Azure Automation Configuration
  2. Data Security on Azure
    • Disk Encryptions
    • Azure AD – RBAC
    • Azure AD – MFA
    • Azure Key Vault

Case scenario discussion and demo: Designing and Implementing Lambda Architecture for a Healthcare Monitoring System

Discussion about the Azure Exam 70-475: Design and Implement Big Data Analytics Solutions

Get Certified: MCSA & MCSE

About The Trainer

Arzan Amaria
Cloud Solutions Architect

arzanArzan has 7+ years of experience in Microsoft Infrastructure technology stack including setting up Windows servers, designing Active Directory and managing various domain services, including Hyper-V virtualization. As a Cloud Solution Architect at CloudThat, he is responsible for deploying, supporting and managing client infrastructures on Azure.Having core training and consulting experience, he is also involved in delivering training to corporate and individuals on Azure.

He holds a MCSE (Server Track) & MCSD: Azure Solutions Architect & Microsoft Certified Trainer & Microsoft Specialist: Architecting Microsoft Azure Solutions (70-534) & Microsoft Specialist: Implementing Microsoft Azure Infrastructure Solutions (70-533) & Microsoft Specialist: Developing Microsoft Azure Solutions (70-532) certification. Other certification include VCA-DCV (Datacenter Virtualization – Associate) &CTT+ (Certified Technology Trainer).

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For latest batch dates, fees, location, technical queries and general inquiries, contact our sales team at: +91 8880002200 or email at

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