Building Your First Data Pipeline in Azure Data Factory
|
Data Engineering is one of the hottest topics on IT right now, as the velocity, volume, and variety of data nowadays require skills beyond just traditional ETL. In this course, you’ll learn the basic concepts needed to work with Azure Data Factory.
Nowadays data is everywhere, and companies are increasingly interested on transforming this data on insights that can help them become more efficient and productive. In this course, Building Your First Data Pipeline in Azure Data Factory, you will learn foundational knowledge on Azure Data Factory, Microsoft’s main response to Data Engineering in the cloud. First, you will learn the concepts needed to create your own pipelines. Next, you will be introduced to data movement and transformation on ADF. Finally, you will see an example of using Data Factory to orchestrate activities to external compute resources. When you are finished with this course, you will have the skills and knowledge of Azure Data Factory needed to understand data movement, orchestration, and transformation activities.
Author Name: Emilio Melo
Author Description:
Emilio Melo is a globetrotting IT professional with projects in over 15 countries, mostly focused on Microsoft software. After 15 years of On Premises experience in Infrastructure, Data and Collaboration, he became fascinated by Cloud technologies and the incredible transformation potential it brings.
Table of Contents
- Course Overview
1min - Understanding Azure Data Factory and Its Interface
29mins - Using Azure Data Factory for ETL Operations
30mins - Using Azure Data Factory for Orchestration
7mins
User Reviews
Be the first to review “Building Your First Data Pipeline in Azure Data Factory”
Related Products
Data Ingestion with Kafka and Kafka Streaming
Learn how to build real-time data ingestion pipelines using Apache Kafka.
Explore fundamentals of large-scale analytics
Organizations use analytics platforms to build large scale data analytics solutions that generate insights and drive success. Microsoft provides multiple technologies that you can combine to build a large scale data analytics solution.
Use Azure Synapse serverless SQL pools to transform data in a data lake
By using a serverless SQL pool in Azure Synapse Analytics, you can use the ubiquitous SQL language to transform data in files in a data lake.
Data Engineering with Microsoft Azure
Explore data engineering concepts on Microsoft Azure’s cloud platform.
Secure data and manage users in Azure Synapse serverless SQL pools
Learn how you can set up security when using Azure Synapse serverless SQL pools
Spark and Data Lakes
Learn how to process big data using Apache Spark and manage data lakes.
There are no reviews yet.