Data is a critical asset for businesses that helps them successfully plan, strategize and execute a wide range of operations. Therefore, data engineering is critical to the overall enterprise data strategy as it helps create the data analysis system. However, this makes it challenging to implement as data engineers must create a system that can ingest raw data from multiple sources and create relevant insights.

Microsoft Azure makes things easier for data engineers by offering a fully managed infrastructure. From data storage to migration and integration, Azure takes care of almost every primary task for professionals and also simplifies the workflow. This E-guide will increase your understanding of how data engineering can be implemented and streamlined with the help of Azure. With this e-guide, you can learn the following:

  • The Major Components of Azure Data Factory (ADF)
  • A Comparison of Azure Data Factory Against Other Data Tools
  • Azure Data Factory Features
  • Business Benefits of ADF
  • Overview of the ETL (Extract-Load-Transform) Process
  • Use cases for Azure Data Factory

We provide detailed step-by-step guidance and screenshots so that implementing pipelines with Azure Data Factory is a breeze.

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