Perform code-free transformation at scale with Azure Data Factory or Azure Synapse Pipeline
|
In this module, you will learn how to perform common data transformation and cleansing activities within Azure Data Factory without using code.
Introduction, Explain Data Factory transformation methods, Describe Data Factory transformation types, Use Data Factory mapping data flow, Debug mapping data flow, Use Data Factory wrangling data, Use compute transformations within Data Factory, Integrate SQL Server Integration Services packages within Data Factory, Knowledge check, Summary
Prerequisites
The student should be able to:
Log into the Azure portal
Explain and create resource groups
Describe Azure Data Factory core components
Ingest data into Azure Data Factory using the Copy Activity
User Reviews
Be the first to review “Perform code-free transformation at scale with Azure Data Factory or Azure Synapse Pipeline”
Related Products
Perform data engineering with Azure Synapse Apache Spark Pools
Apache Spark is a highly scalable distributed processing solution for big data analytics and transformation. You can leverage its power in Azure Synapse Analytics by using Spark pools.
Data Engineering with Microsoft Azure
Explore data engineering concepts on Microsoft Azure’s cloud platform.
Transfer and transform data with Azure Synapse Analytics pipelines
Azure Synapse Analytics enables data integration through the use of pipelines, which you can use to automate and orchestrate data transfer and transformation activities.
Use Delta Lake in Azure Synapse Analytics
Delta Lake is an open source relational storage area for Spark that you can use to implement a data lakehouse architecture in Azure Synapse Analytics.
Data Engineering
Learn how to build, optimize, and maintain data pipelines for data processing and storage.
Data lakes and Lakehouses with Spark and Azure Databricks
Learn to manage and process data using Spark and Azure Databricks platforms.
There are no reviews yet.