Azure Data Engineering Full Tutorial | What Is Azure Data Engineer | Eclasess

Azure Data Engineering Full Tutorial | Bangalore | Comprehensive Guide for Beginners to Advanced
Welcome to our complete guide on Azure Data Engineering! Whether you're a beginner looking to dive into data engineering or an experienced professional seeking to sharpen your skills, this tutorial is tailored for you. In this video, we cover everything you need to know about data engineering on Microsoft Azure.
🔹 What You'll Learn:
Introduction to Azure Data Engineering: Understand the basics of data engineering on Azure and its importance.
Azure Data Services Overview: Dive into core services like Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, and Azure SQL Database.
Data Ingestion & Integration: Learn how to ingest data from various sources using Azure Data Factory and integrate it seamlessly.
Data Storage Solutions: Explore options for storing data, including Azure Data Lake Storage and Azure Blob Storage.
Data Transformation & Processing: Get hands-on with data transformation using Azure Data Factory, Databricks, and Azure Synapse.
Data Analytics & Visualization: Discover how to analyze and visualize data using Azure Synapse Analytics and Power BI.
Best Practices & Optimization: Learn best practices for optimizing your data workflows and ensuring scalability.
📍 Location: Bangalore This tutorial is specially tailored for professionals and enthusiasts in Bangalore, providing localized examples and insights relevant to the region’s data landscape.
💻 Who Should Watch:
Data Engineers
Data Scientists
Cloud Enthusiasts
IT Professionals
Students & Fresh Graduates
🔗 Resources & Links:
Azure Data Factory Documentation
Azure Data Lake Storage Overview
Azure Synapse Analytics
Microsoft Learn: Data Engineering on Azure
📅 Timestamped Sections: 0:00 - Introduction 2:30 - Overview of Azure Data Services 6:00 - Data Ingestion with Azure Data Factory 12:45 - Storing Data in Azure 20:15 - Data Transformation with Azure Databricks 30:00 - Data Analytics & Visualization with Power BI 40:00 - Best Practices & Optimization Tips 45:30 - Q&A and Wrap-up
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