Microsoft Azure Big Data Analytics Course Overview

Microsoft Azure Big Data Analytics Course Overview

The Microsoft Azure Big Data Analytics course is designed for professionals who want to learn how to build and deploy big data analytics solutions in the Azure cloud. This course offers a deep dive into designing both batch and real-time data processing solutions, operationalizing end-to-end analytics, and leveraging PowerShell for automation and administration.

Module 1 focuses on designing big data solutions, including data ingestion and batch processing techniques, while Module 2 shifts to real-time processing, highlighting data ingestion strategies and query design. Module 3 is about operationalizing cloud analytics, teaching students how to create data factories, manage workflows, and design deployment strategies. For tech professionals, Module 4 enriches their skills in PowerShell, comparing it with other scripting languages, and guiding them through script creation and administration tasks.

Learners will benefit from practical labs, which consolidate the theoretical knowledge into actionable skills. By the end of the course, participants will be capable of implementing robust big data analytics solutions on Azure, thus enhancing their expertise in the field of cloud computing and data analytics.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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Course Prerequisites

Certainly, here are the minimum required prerequisites for successfully undertaking training in the Microsoft Azure Big Data Analytics course:

  • Basic understanding of cloud computing concepts, particularly Microsoft Azure.
  • Familiarity with data processing concepts and data processing technologies.
  • Knowledge of core data concepts, such as relational databases, non-relational databases, and data analysis.
  • Experience with any programming or scripting language (preferably PowerShell, Python, or similar) for the optional PowerShell module.
  • Basic experience with Microsoft Azure services like Azure Storage, Azure SQL Database, and Azure Cosmos DB is beneficial.
  • Understanding of batch and real-time data processing patterns is helpful but not mandatory.
  • An interest in learning how to operationalize end-to-end cloud analytics solutions.

Please note that while these prerequisites are designed to help you get the most out of the course, motivated learners with less experience are welcome and will find that the course provides a comprehensive introduction to the necessary concepts and skills.

Target Audience for Microsoft Azure Big Data Analytics

The Microsoft Azure Big Data Analytics course is designed for professionals seeking expertise in cloud analytics and big data solutions.

  • Data Scientists
  • Data Analysts
  • Data Engineers
  • Cloud Solution Architects
  • Azure Developers
  • Big Data Specialists
  • IT Professionals interested in big data and analytics
  • Database Managers and Administrators
  • Business Intelligence Professionals
  • System Administrators with a focus on scripting and automation
  • Professionals looking to learn about real-time data processing
  • Technical Team Leads managing big data infrastructure
  • DevOps Engineers involved in deployment strategies for big data solutions
  • Professionals preparing for Microsoft Azure certification exams

Learning Objectives - What you will Learn in this Microsoft Azure Big Data Analytics?

Introduction to Learning Outcomes

This Microsoft Azure Big Data Analytics course equips students with the knowledge to design, operationalize, and manage analytics solutions on Azure, focusing on batch and real-time data processing.

Learning Objectives and Outcomes

  • Understand the process of ingesting data for batch and real-time processing on Azure.
  • Learn to design robust batch processing solutions for large-scale data analytics.
  • Gain skills to construct interactive queries to extract insights from big data.
  • Acquire the ability to design and implement real-time data processing solutions using Azure tools.
  • Develop competencies in creating and managing Azure Data Factory instances and workflows.
  • Master techniques for monitoring, managing, and troubleshooting data pipelines within Azure ecosystems.
  • Explore strategies for moving, transforming, and analyzing data effectively in the cloud.
  • Learn to design and deploy end-to-end cloud analytics solutions for optimal performance and scalability.
  • Gain insights into using PowerShell for administering and automating tasks in Azure.
  • Understand best practices for resolving scripting problems and administering resources using PowerShell.