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Microsoft

Data Integration with Microsoft Azure Data Factory

Microsoft via Coursera

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Overview

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In this course, you will learn how to create and manage data pipelines in the cloud using Azure Data Factory. This course is part of a Specialization intended for Data engineers and developers who want to demonstrate their expertise in designing and implementing data solutions that use Microsoft Azure data services. It is ideal for anyone interested in preparing for the DP-203: Data Engineering on Microsoft Azure exam (beta). This is the third course in a program of 10 courses to help prepare you to take the exam so that you can have expertise in designing and implementing data solutions that use Microsoft Azure data services. The Data Engineering on Microsoft Azure exam is an opportunity to prove knowledge expertise in integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions that use Microsoft Azure data services. Each course teaches you the concepts and skills that are measured by the exam. By the end of this Specialization, you will be ready to take and sign-up for the Exam DP-203: Data Engineering on Microsoft Azure (beta).

Syllabus

  • Integrate data with Azure Data Factory or Azure Synapse Pipeline
    • Describe the core components of Azure Data Factory that enable you to create large scale data ingestion solutions in the cloud
  • Petabyte-scale ingestion with Azure Data Factory or Azure Synapse Pipeline
    • Describe the various methods that can be used to ingest data between various data stores using Azure Data Factory
  • Perform code-free transformation at scale with Azure Data Factory or Azure Synapse Pipeline
    • Perform common data transformation and cleansing activities within Azure Data Factory without using code Implement Slowly Changing Dimension using Azure Data Factory or Azure Synapse Pipelines
  • Orchestrate data movement and transformation in Azure Data Factory or Azure Synapse Pipeline
    • Use Azure Data Factory to orchestrate large scale data movement by using other Azure Data Platform and Machine Learning technologies
  • Execute existing SSIS packages in Azure Data Factory or Azure Synapse Pipeline
    • Integrate SQL Server Integration Services packages into an Azure Data Factory solution
  • Operationalize your Azure Data Factory or Azure Synapse Pipeline
    • Publish your Azure Data Factory work between different environments
  • Receive data with Azure Data Share and transforming with Azure Data Factory
    • Ingest data from Azure Data Share into Azure Data Factory pipelines to build automated ingestion pipelines
  • Course Practice Exam
    • Practice Exam on Data integration at scale with Azure Data Factory or Azure Synapse Pipeline

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Microsoft

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3.8 rating at Coursera based on 162 ratings

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