Integrate data with Azure Data Factory or Azure Synapse Pipeline
|
In this module, you’ll examine Azure Data Factory and the core components that enable you to create large scale data ingestion solutions in the cloud
Understand Azure Data Factory, Describe data integration patterns, Explain the data factory process, Understand Azure Data Factory components, Azure Data Factory security, Set up Azure Data Factory, Create linked services, Create datasets, Create data factory activities and pipelines, Manage integration runtime
Prerequisites
The student should be able to:
Log in to the Azure portal
Explain and create resource groups
User Reviews
Be the first to review “Integrate data with Azure Data Factory or Azure Synapse Pipeline”
Related Products
Data Streaming
Study techniques for real-time data processing and stream analytics.
Create a lake database in Azure Synapse Analytics
Why choose between working with files in a data lake or a relational database schema? With lake databases in Azure Synapse Analytics, you can combine the benefits of both.
Use Apache Spark in Azure Databricks
Azure Databricks is built on Apache Spark and enables data engineers and analysts to run Spark jobs to transform, analyze and visualize data at scale.
Introduction to Azure Data Lake Storage Gen2
Data lakes are a core element of data analytics architectures. Azure Data Lake Storage Gen2 provides a scalable, secure, cloud-based solution for data lake storage.
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.
Load data into a relational data warehouse
A core responsibility for a data engineer is to implement a data ingestion solution that loads new data into a relational data warehouse.
There are no reviews yet.