Azure Data Engineering Free Tutorial ||Full Course ||Certification || Interview Q & A || Telugu

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Embark on a thrilling data engineering journey with Microsoft Azure! Join our power-packed 3-hour YouTube course where we'll guide you through the ins and outs of Azure Data Engineering, empowering you with essential skills for conquering the world of data management and analytics.

Topics Covered:

Cloud Computing and Advantages
Different Courses Offered by Azure
Roles and Responsibilities of Azure Data Engineer
Services and Topics Covered as Azure Data Engineer
Job Market for Azure Data Engineer
Prerequisites to Learn Azure Data Engineer
Course Duration: 45 hours (2 months, daily 1 Hour session

Course Particulars:

Project End to End
Practical Sessions
Daily Class Notes
Daily Recording Videos
Live Sessions
Hands-on Projects
Certification Preparation
Course Completion Certificate
Join us on this exciting Azure Data Engineering journey, and let's explore the vast opportunities in the world of data engineering together! Don't forget to like, share, and subscribe to our channel for more valuable content. See you in class!

An Azure Data Engineer is a professional responsible for designing and implementing the management, monitoring, security, and privacy of data using the wide array of Azure services. They leverage these services to build robust data solutions in the cloud. Here's a breakdown of the services you'll be covering:

Introduction To Microsoft Azure: Understanding Azure's core concepts, services, and its significance in cloud computing.

Azure Storage Account: Exploring Azure's storage solutions, including Blob storage, File storage, Queue storage, and Table storage.

Azure Data Lake: Understanding and utilizing Azure Data Lake Storage for scalable and secure data storage and analytics.

Azure SQL: Managing relational databases in Azure using Azure SQL Database, which offers intelligent features and global scalability.

Azure Synapse Analytics: Leveraging this analytics service to explore and analyze massive volumes of data using a unified experience for big data and data warehousing.

Azure Data Factory: Designing and orchestrating data workflows through the cloud using Azure Data Factory for ETL (Extract, Transform, Load) processes.

Azure Databricks with PySpark: Implementing big data analytics and AI solutions using Azure Databricks with the PySpark framework.
Introduction to Power BI: Exploring the capabilities of Power BI for data visualization and business intelligence.

Design Report using Power BI: Utilizing Power BI services to create insightful reports and dashboards from diverse data sources.

By covering these services hands-on in Telugu, you're offering learners a practical understanding of how to utilize these Azure services effectively to manage, process, and derive insights from data in the cloud. This comprehensive approach equips learners with the skills needed to excel as Azure Data Engineers in the field of data management and analytics within Microsoft Azure.

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