Description
Azure Data Factory (ADF): Build Scalable Data Pipelines is a course on how to design, implement, and manage robust ETL and data integration pipelines using Azure Data Factory published by Udemy Online Academy. This is a comprehensive course that teaches learners how to design, implement, and manage robust ETL and data integration pipelines using Microsoft Azure Data Factory. This course is ideal for data engineers, analysts, and IT professionals who want to build scalable, efficient, and automated workflows for cloud-based data processing.
This course covers the fundamentals of ADF, including data ingestion, transformation, and synchronization, while also exploring pipelines, datasets, and related services. Learners gain hands-on experience building scalable ETL workflows, integrating multiple data sources, and implementing data transformation and transformation strategies. It also covers planning, monitoring, fault management, and optimization techniques to ensure reliable and efficient operations. Advanced modules cover parameterization, dynamic pipelines, and integration with Azure Synapse, Databricks, and other services for end-to-end data solutions. By the end, individuals will be able to create automated, scalable, and maintainable data pipelines that support complex analytics and business intelligence needs in cloud environments.
What you will learn in Azure Data Factory (ADF): Build Scalable Data Pipelines:
- Explain the basics of Azure Data Factory (ADF) and its role in the Azure cloud ecosystem.
- Understand the concepts, services, and data types related to enterprise data integration.
- Identify and configure the core components of ADF, including related services, datasets, pipelines, and triggers.
- Perform data ingest and migration tasks, such as copying data to Azure Blob Storage, ADLS Gen2, SQL databases, and internal sources.
- Analyze and manage copy activity behavior to optimize data migration efficiency and reliability.
- Implement parameterization in ADF pipelines using related services, datasets, and variables for reusability and dynamic configurations.
- Perform advanced copy operations, such as bulk data migration, file count-based activities, and multi-file ingest scenarios.
- Use stored procedures and SQL queries in ADF pipelines to transform and manage data streams.
- Transform and transform structured data formats (such as CSV to JSON) using ADF data streams.
- Implement security best practices by integrating Azure Key Vault for secret management and secure credential management.
- Design and implement various data loading strategies, including full loading, incremental (delta) loading, and hybrid approaches.
- Integrate external APIs and services into ADF pipelines to extend data movement and transformation capabilities.
- Streamline hybrid and multi-cloud data workflows by connecting ADF to AWS, Google Cloud, and on-premises systems.
- Schedule, monitor, and automate pipelines using triggers and scheduling features in ADF.
- And…
Course specifications
Publisher: Udemy
Instructors: Uplatz Training
Language: English
Level: Introductory to Advanced
Number of Lessons: 41
Duration: 31 hours and 1 minutes
Course topics
Azure Data Factory (ADF): Build Scalable Data Pipelines Prerequisites
Enthusiasm and determination to make your mark on the world!
Pictures
Azure Data Factory (ADF): Build Scalable Data Pipelines introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 720p
Download link
Downloadly
Rapidgator
Password File(s): www.downloadly.ir
Size
13.7 GB
