Microsoft Azure Data Engineering Training Course

You don’t need to possess any predefined skills or expertise to enroll in this course. However, any prior knowledge of Linux, Python, SQL, and Scala would be beneficial.

Our Certification Training course is designed according to industry standards and helps learners design, implement, and maintain secure and compliant data processing pipelines using Azure data services and frameworks.

As a Certified Azure Data Engineer, several skills are essential for success. Here are some of the most important skills you will need:

Anyone with a zeal to learn and who wants to become a Data Engineer or Data Architect can join this training.

You need a basic configuration with a minimum of 4GB RAM and i3 processor, with a good internet connection.

You will be using an Azure Free Tier Account to execute the practicals. The detailed, step-by-step installation guides are available on the LMS. Edureka's 24*7 technical support team is always available to promptly assist you with your queries.

You can enroll in this online training on our website and make an online payment using any of the following options:

Learn to implement and manage data engineering workloads on Microsoft Azure using key services like Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and more.

Learning Azure Data Engineering is essential for building scalable, cloud-based data solutions that enable businesses to process, analyze, and derive insights from vast amounts of data. It provides professionals with knowledge of data integration, transformation, cloud computing, big data analytics, and enterprise data solutions. As organizations increasingly rely on data-driven decision-making, Azure Data Engineering skills are highly valuable for future career growth.

Yes, coding is required for an Azure Data Engineer, though the level varies by role. Key areas include SQL for data transformation in Azure Synapse Analytics and Azure SQL Database, PySpark or Scala for big data processing in Azure Databricks, Python or PowerShell for automation in Azure Data Factory and Azure Functions, JavaScript or SQL-like languages for real-time streaming in Azure Stream Analytics, and ARM templates, Terraform for Infrastructure as Code (IaC).

Both Azure and AWS offer robust data engineering solutions, but their strengths differ.AWS is suited for large-scale, high-volume data processing with worldwide reach. In contrast, Azure is distinguished by its seamless connection with Microsoft services and user-friendly, low-code tools that make deployment and development easier. The choice depends on project needs, existing infrastructure, and personal or organizational preferences.

Becoming an Azure Data Engineer is a great career choice due to the growing demand for cloud-based data solutions. With Azure's widespread adoption in enterprises, certified professionals can access high-paying job opportunities and play a crucial role in driving data-driven decision-making across industries.

Yes, data engineering has a strong future as businesses rely on big data, AI, and cloud computing. Skilled data engineers are in high demand to build and optimize data pipelines, making it a promising and future-proof career.

Yes, becoming an Azure Data Engineer is a great career option due to the increasing demand for data-driven decision-making in businesses. With expertise in cloud-based data solutions, pipeline development, and data management, Azure Data Engineers play a crucial role in modern enterprises, offering strong career growth and job opportunities.

All trainers are industry experts, Microsoft Certified, and have over 12 years of experience in training and working in the domain.