Modern Data Engineering with Microsoft Fabric Course Overview

Modern Data Engineering with Microsoft Fabric Course Overview

Unlock the power of Modern Data Engineering with Microsoft Fabric through our comprehensive course. Designed for both aspiring and experienced data professionals, this course covers essential topics such as data integration, pipeline development, and real-time analytics. You will learn to utilize Microsoft Fabric’s advanced tools to efficiently manage data flows and optimize data architecture.

By the end of the course, you will be able to implement best practices in data engineering, ensuring your projects are scalable and efficient. Engage in hands-on projects that reinforce the concepts learned, equipping you with the practical skills necessary to excel in today’s data-driven landscape. Join us to stay ahead in the evolving field of data engineering!

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1,150

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Course Fee 1,150
Total Fees
1,150 (USD)
  • Live Training (Duration : 24 Hours)
  • Per Participant
  • Guaranteed-to-Run (GTR)
  • Classroom Training fee on request

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  • Live Training (Duration : 24 Hours)
  • Per Participant
  • Classroom Training fee on request

♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

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Course Advisor

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Prem Nidhi Sharma

9+ Years Experience

An effective communicator with good analytical, problem-solving, and organizational abilities. I enjoy interacting with people and providing solutions to their needs. I am an expert in making Training a Fun and learning experience. 

 

I am a seasoned Technical Lead with a strong foundation in data engineering and cloud technologies, holding certifications as a Microsoft Certified Data Engineer and Fabric Analytics Engineer. With a robust background as a Database Administrator across both on-premises and Azure cloud environments, I bring deep expertise in enterprise-scale data solutions.

My technical skill set includes hands-on experience with SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS), and SQL Server Reporting Services (SSRS), along with advanced proficiency in Azure Databricks and end-to-end database development. I have successfully designed and implemented complex data architectures and analytics platforms that drive business insights and operational efficiency.

In addition to my technical acumen, I have had the privilege of training and consulting for leading global IT service providers such as HCL, Wipro, Cognizant, and Infosys, helping teams adopt best practices and leverage modern data tools effectively.

I am passionate about building scalable data ecosystems, mentoring cross-functional teams, and delivering innovative solutions that align with strategic business goals.

 

Target Audience for Modern Data Engineering with Microsoft Fabric

The Modern Data Engineering with Microsoft Fabric course equips professionals with essential skills to leverage Microsoft Fabric for data integration, analytics, and management. It's ideal for those looking to enhance their data engineering capabilities.


Target Audience:


  • Data Engineers
  • Data Analysts
  • Business Intelligence Developers
  • ETL Developers
  • Data Architects
  • Cloud Solution Architects
  • Database Administrators
  • IT Professionals focusing on data solutions
  • Software Engineers working with data platforms
  • Aspiring Data Professionals and Students
  • Project Managers overseeing data-centric projects


Learning Objectives - What you will Learn in this Modern Data Engineering with Microsoft Fabric?

Course Introduction

The Modern Data Engineering with Microsoft Fabric course equips students with practical skills in data engineering, enabling them to design, build, and manage scalable data solutions using Microsoft Fabric's advanced capabilities.

Learning Objectives and Outcomes

  • Understand the architecture of Microsoft Fabric and its components.
  • Develop data ingestion pipelines to securely collect data from various sources.
  • Implement data transformations using data flow and transformation features.
  • Design and manage data storage solutions for scalability and performance.
  • Utilize analytics tools for data visualization and reporting.
  • Integrate machine learning capabilities within data workflows.
  • Ensure data governance and compliance across data engineering processes.
  • Optimize data pipelines for performance and cost-efficiency.
  • Monitor and troubleshoot data workflows effectively.
  • Collaborate within teams using Azure DevOps for agile project management.

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