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Azure Big Data Analytics Training

Training

Dates: Available on Request
Locations: Johannesburg, South Africa
Platform: Available In-Class

Price: Available on request

Course Introduction

Microsoft Azure is a cloud computing service built by Microsoft for creating, testing, deploying, and managing applications through data centres managed by Microsoft.

 

This Azure Big Data certification course covers various cloud analytics options available on the Microsoft Azure cloud platform. It includes detailed studies of data analytics services like HDInsight, Apache Spark, Jupiter, Zeppelin, Stream Analytics, and Lake Analytics.

 

Most organizations today seek deeper analysis of accessible data to enhance their decision-making process and increase the probability of success. Azure analytics services help you derive useful insights from big data, whether it is real-time or gathered over time.

 

Prerequisites

Although not mandatory, participants are expected to have a basic understanding of:

  • Big data

  • Data analytics

  • Processing and querying bulk data

  • Analysing real-time and historical data

  • Using SQL

  • Data analysis and visualization tools like Power BI or PowerShell

Course Objectives

Upon successfully completing this Azure Big Data certification course, participants will be able to:

  • Get an overview of the big data and advanced analytics capabilities of the cloud

  • Explore various Big Data Analytics services available on Microsoft Azure cloud

  • Recognize how to design solutions for batch and real-time data processing

  • Understand different methods of using Azure

  • Expand their knowledge about creating big data analytics solutions on Microsoft Azure

  • Learn HDInsight, Apache Spark, Jupiter, Zeppelin, Stream Analytics, Lake Analytics, Data Bricks

Who should attend?

This Azure Big Data certification course is suitable for:

  • Those who want a career in Cloud Computing and Data Analytics

  • Anyone interested in learning Microsoft Azure

  • Individuals interested in learning about various Big Data Analytics services and options available on Microsoft Azure

  • Software Architects

  • Programming Developers and System Administrators

  • Experienced working professionals and Project Managers

  • Business Intelligence, Data Warehousing, and Analytics Professionals

  • ETL and Data Warehousing Professionals

  • Data Analysts & Business Intelligence Professionals

  • Database Administrators and other DB professionals

IT and Records Courses

Training Methodology

Our diverse instructional approaches ensure effective learning:

– Lectures & Presentations: Engage with expert-driven, stimulating content.
– Course Material: Access well-crafted supporting resources.
– Group Work: Collaborate on discussions and case studies for practical insights.
– Workshops & Role-Play: Participate in immersive, scenario-based activities.
– Practical Application: Focus on applying theoretical knowledge in real situations.
– Post-Training Support: Receive extensive support after training for skill implementation.

Training Outline

MODULE 1: BIG DATA BATCH PROCESSING

  • Ingest data for batch processing

  • Design for batch processing

  • Design interactive queries

MODULE 2: DESIGN BIG DATA BATCH PROCESSING SOLUTIONS

  • Load data into Microsoft Azure

  • Prepare data for batch processing

  • Query the data

  • Conclusion

MODULE 3: BIG DATA REAL-TIME PROCESSING SOLUTIONS

  • Ingest data for Real-Time Processing

  • Designing for Real-Time Processing

  • Design interactive queries for Big Data

MODULE 4: DESIGN BIG DATA REAL-TIME PROCESSING SOLUTIONS

  • Load data into Microsoft Azure

  • Prepare data for Real-Time event processing

  • Visualize the Data

  • Conclusion

MODULE 5: OPERATIONALIZE END-TO-END CLOUD ANALYTICS SOLUTIONS

  • Create a data factory

  • Create a data-driven workflow

  • Monitor and manage the data factory

  • Move, transform and analyse data

  • Design a deployment plan for an end-to-end solution

MODULE 6: IMPLEMENTING DATA STORAGE IN AZURE

  • Choosing a data storage mechanism

  • Accessing data in Azure Storage

  • Working with structured data in Azure

  • Geographically distributing data with Azure CDN

  • Scaling with out-of-process cache

  • Storing files in Azure Storage

  • Store publicly accessible files in Azure Blobs

  • Produce and store private files in Azure Blobs

  • Querying graph data with Cosmos DB

  • Create the Cosmos DB graph database

  • Query the Cosmos DB database

  • Caching out-of-process with Azure Redis cache

  • Create the Azure Redis Cache service

  • Access the cache service from code

  • Test the application

MODULE 7: DATA FACTORIES AND WORKFLOWS

  • Create, manage & monitor a data factory

  • Create a data-driven workflow

  • Move, transform and analyse data

  • Create a deployment strategy using PowerShell

MODULE 8: POWERSHELL FOR TECHNOLOGY PROFESSIONALS

  • Compared to other scripting languages

  • Configuring and using PowerShell

  • Creating and running scripts

  • Administering local resources

  • Administering network resources

  • Resolve PowerShell scripting problems

MODULE 9: OPERATIONALIZE END-TO-END CLOUD ANALYTICS SOLUTIONS

  • Use PowerShell to get computer information

  • Use PowerShell to understand and apply cmdlets

  • Create an Azure VM with Azure PowerShell

  • Cortana Intelligence Suite

  • Azure Machine Learning solutions

MODULE 10: SCRIPTING

  • Create and execute scripts

  • Configure and test remote management

  • Additional reading

  • Operationalize Cloud Analytics Solutions with Microsoft Azure

  • Microsoft R and Microsoft R Server

MODULE 11: HDINSIGHT

  • Data Analytics

  • HDInsight

  • HDInsight 3 – Spark

  • HDInsight 4 – Jupiter

  • HDInsight 5 – Zeppelin

MODULE 12: HOSTING SERVICES ON-PREMISES AND IN AZURE

  • Hosting services on-premises

  • Hosting services in Azure App Service

  • Packaging services in containers

  • Implementing serverless services

  • Host an ASP.NET service in Windows

  • Creating a new ASP.NET Core Application

  • Registering the Windows service

  • Host an ASP.NET Web API in an Azure Web App

  • Install an ASP.NET Web API to the Web App

  • Host an ASP.NET service in Azure Container Instances

  • Publish the service to a Docker container

  • Host the service in Azure Container Instances

  • Implement an Azure Function

  • Develop the service locally

  • Deploy the service to Azure Functions

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